modelId
stringlengths 4
122
| author
stringlengths 2
42
⌀ | last_modified
timestamp[us, tz=UTC] | downloads
int64 0
74.7M
| likes
int64 0
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| library_name
stringlengths 2
84
⌀ | tags
list | pipeline_tag
stringlengths 5
30
⌀ | createdAt
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| embedding
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|---|---|---|---|---|---|---|---|---|---|---|
tkcho/commerce-clf-kr-sku-brand-68285f88f36e02259b8269727926353d
|
tkcho
| 2023-11-22T12:02:12Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T12:01:37Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b64e68730bae6d53e86af7e5583050fa
|
tkcho
| 2023-11-22T14:04:07Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T14:03:38Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-4ef9dae683497c5fefb4fb48b84e5bc4
|
tkcho
| 2023-11-22T16:12:21Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T16:11:51Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-5de80cd88638d94e397d0a63689ccce1
|
tkcho
| 2023-11-23T07:10:35Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T07:09:57Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-a88462922d0c62e8e58fe1992e6615a9
|
tkcho
| 2023-11-24T01:34:04Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T01:33:30Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-95840d7e25901d24d725ad873f760953
|
tkcho
| 2023-11-24T05:38:41Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T05:38:06Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-190cf74ce12f108d2f92dbb13662b936
|
tkcho
| 2023-11-24T09:59:10Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T09:58:41Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-4d51e89b3e6cf4fd98f6f8e5292d28fe
|
tkcho
| 2023-11-24T12:59:52Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T12:59:23Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-976a878a2218e3c6f84f0c21310e4a8b
|
tkcho
| 2023-11-24T20:41:14Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T20:40:46Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-9136be42a4e55145b2d1a88180d3f360
|
tkcho
| 2023-11-25T02:37:43Z | 4,438 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-25T02:37:11Z |
Entry not found
|
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] |
Phind/Phind-CodeLlama-34B-Python-v1
|
Phind
| 2023-08-26T03:05:48Z | 4,437 | 240 |
transformers
|
[
"transformers",
"pytorch",
"llama",
"text-generation",
"code llama",
"license:llama2",
"model-index",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-08-25T20:33:09Z |
---
license: llama2
model-index:
- name: Phind-CodeLlama-34B-v1
results:
- task:
type: text-generation
dataset:
type: openai_humaneval
name: HumanEval
metrics:
- name: pass@1
type: pass@1
value: 69.5%
verified: false
tags:
- code llama
---
# **Phind-CodeLlama-34B-Python-v1**
We've fine-tuned CodeLlama-34B and CodeLlama-34B-Python on an internal Phind dataset that achieve 67.6% and 69.5% pass@1 on HumanEval, respectively. GPT-4 achieves 67%. We've applied OpenAI's decontamination methodology to our dataset to ensure result validity.
More details can be found on our [blog post](https://www.phind.com/blog/code-llama-beats-gpt4).
## Model Details
This model is fine-tuned from CodeLlama-34B-Python and achieves 69.5% pass@1 on HumanEval.
## Dataset Details
We fined-tuned on a proprietary dataset of ~80k high quality programming problems and solutions. This dataset consists of instruction-answer pairs instead of code completion examples, making it structurally different from HumanEval. The Phind models were trained for 2 epochs, for a total of ~160k examples shown. LoRA was not used -- both models are a native finetune. We used DeepSpeed ZeRO 3 and Flash Attention 2 to train these models in three hours on 32 A100-80GB GPUs. We used a sequence length of 4096 tokens.
## How to Get Started with the Model
Make sure to install Transformers from the main git branch:
```bash
pip install git+https://github.com/huggingface/transformers.git
```
## How to Prompt the Model
**Please note that this model is somewhat instruction-tuned, but not chat-tuned.**
Do not try to use the Llama chat markup with this model. Instead, simply tell it what you want and add "\n: " at the end of your task.
For example:
```
Write me a linked list implementation: \n
```
## How to reproduce HumanEval Results
To reproduce our results:
```python
from transformers import AutoTokenizer, LlamaForCausalLM
from human_eval.data import write_jsonl, read_problems
from tqdm import tqdm
# initialize the model
model_path = "Phind/Phind-CodeLlama-34B-v1"
model = LlamaForCausalLM.from_pretrained(model_path, device_map="auto")
tokenizer = AutoTokenizer.from_pretrained(model_path)
# HumanEval helper
def generate_one_completion(prompt: str):
tokenizer.pad_token = tokenizer.eos_token
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=4096)
# Generate
generate_ids = model.generate(inputs.input_ids.to("cuda"), max_new_tokens=256, do_sample=True, top_p=0.75, top_k=40, temperature=0.1)
completion = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
completion = completion.replace(prompt, "").split("\n\n\n")[0]
return completion
# perform HumanEval
problems = read_problems()
num_samples_per_task = 1
samples = [
dict(task_id=task_id, completion=generate_one_completion(problems[task_id]["prompt"]))
for task_id in tqdm(problems)
for _ in range(num_samples_per_task)
]
write_jsonl("samples.jsonl", samples)
# run `evaluate_functional_correctness samples.jsonl` in your HumanEval code sandbox
```
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
This model has undergone very limited testing. Additional safety testing should be performed before any real-world deployments.
## Training details
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
- **Hardware Type:** 32x A100-80GB
- **Hours used:** 90 GPU-hours
- **Cloud Provider:** AWS
- **Compute Region:** us-east-1
|
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] |
deepseek-ai/deepseek-coder-6.7b-base
|
deepseek-ai
| 2023-11-05T10:26:13Z | 4,437 | 28 |
transformers
|
[
"transformers",
"pytorch",
"llama",
"text-generation",
"license:other",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-10-23T16:15:39Z |
---
license: other
license_name: deepseek-license
license_link: LICENSE
---
<p align="center">
<img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder]</a> | <a href="https://discord.gg/Tc7c45Zzu5">[Discord]</a> | <a href="https://github.com/guoday/assert/blob/main/QR.png?raw=true">[Wechat(微信)]</a> </p>
<hr>
### 1. Introduction of Deepseek Coder
Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks.
- **Massive Training Data**: Trained from scratch on 2T tokens, including 87% code and 13% linguistic data in both English and Chinese languages.
- **Highly Flexible & Scalable**: Offered in model sizes of 1.3B, 5.7B, 6.7B, and 33B, enabling users to choose the setup most suitable for their requirements.
- **Superior Model Performance**: State-of-the-art performance among publicly available code models on HumanEval, MultiPL-E, MBPP, DS-1000, and APPS benchmarks.
- **Advanced Code Completion Capabilities**: A window size of 16K and a fill-in-the-blank task, supporting project-level code completion and infilling tasks.
### 2. Model Summary
deepseek-coder-6.7b-base is a 6.7B parameter model with Multi-Head Attention trained on 2 trillion tokens.
- **Home Page:** [DeepSeek](https://deepseek.com/)
- **Repository:** [deepseek-ai/deepseek-coder](https://github.com/deepseek-ai/deepseek-coder)
- **Chat With DeepSeek Coder:** [DeepSeek-Coder](https://coder.deepseek.com/)
### 3. How to Use
Here give some examples of how to use our model.
#### 1）Code Completion
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
input_text = "#write a quick sort algorithm"
inputs = tokenizer(input_text, return_tensors="pt").cuda()
outputs = model.generate(**inputs, max_length=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
#### 2）Code Insertion
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
input_text = """<｜fim▁begin｜>def quick_sort(arr):
if len(arr) <= 1:
return arr
pivot = arr[0]
left = []
right = []
<｜fim▁hole｜>
if arr[i] < pivot:
left.append(arr[i])
else:
right.append(arr[i])
return quick_sort(left) + [pivot] + quick_sort(right)<｜fim▁end｜>"""
inputs = tokenizer(input_text, return_tensors="pt").cuda()
outputs = model.generate(**inputs, max_length=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True)[len(input_text):])
```
#### 3）Repository Level Code Completion
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-base", trust_remote_code=True).cuda()
input_text = """#utils.py
import torch
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import accuracy_score
def load_data():
iris = datasets.load_iris()
X = iris.data
y = iris.target
# Standardize the data
scaler = StandardScaler()
X = scaler.fit_transform(X)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
# Convert numpy data to PyTorch tensors
X_train = torch.tensor(X_train, dtype=torch.float32)
X_test = torch.tensor(X_test, dtype=torch.float32)
y_train = torch.tensor(y_train, dtype=torch.int64)
y_test = torch.tensor(y_test, dtype=torch.int64)
return X_train, X_test, y_train, y_test
def evaluate_predictions(y_test, y_pred):
return accuracy_score(y_test, y_pred)
#model.py
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset
class IrisClassifier(nn.Module):
def __init__(self):
super(IrisClassifier, self).__init__()
self.fc = nn.Sequential(
nn.Linear(4, 16),
nn.ReLU(),
nn.Linear(16, 3)
)
def forward(self, x):
return self.fc(x)
def train_model(self, X_train, y_train, epochs, lr, batch_size):
criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(self.parameters(), lr=lr)
# Create DataLoader for batches
dataset = TensorDataset(X_train, y_train)
dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
for epoch in range(epochs):
for batch_X, batch_y in dataloader:
optimizer.zero_grad()
outputs = self(batch_X)
loss = criterion(outputs, batch_y)
loss.backward()
optimizer.step()
def predict(self, X_test):
with torch.no_grad():
outputs = self(X_test)
_, predicted = outputs.max(1)
return predicted.numpy()
#main.py
from utils import load_data, evaluate_predictions
from model import IrisClassifier as Classifier
def main():
# Model training and evaluation
"""
inputs = tokenizer(input_text, return_tensors="pt").cuda()
outputs = model.generate(**inputs, max_new_tokens=140)
print(tokenizer.decode(outputs[0]))
```
### 4. License
This code repository is licensed under the MIT License. The use of DeepSeek Coder models is subject to the Model License. DeepSeek Coder supports commercial use.
See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-coder/blob/main/LICENSE-MODEL) for more details.
### 5. Contact
If you have any questions, please raise an issue or contact us at [[email protected]](mailto:[email protected]).
|
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] |
tkcho/commerce-clf-kr-sku-brand-4888c131518ac868306a9106b7dcaaf8
|
tkcho
| 2023-11-27T18:53:00Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-14T19:48:23Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cda24905767dd53008054299320ebd96
|
tkcho
| 2023-11-28T12:40:36Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T09:08:14Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-743d1a1172edfa64e699e1538c609a0f
|
tkcho
| 2023-11-15T16:17:46Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T16:17:19Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-4537fbaf67264d47757c6ef2d0caf88c
|
tkcho
| 2023-11-17T09:48:35Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T09:48:07Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-ccc24a1803afc28ee709d823f8c80f05
|
tkcho
| 2023-11-17T14:42:57Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T14:42:26Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-de88789619e97d9558bc1917273094e8
|
tkcho
| 2023-11-18T14:20:22Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T14:19:50Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-44ea7383793ca36f67051b37c4993996
|
tkcho
| 2023-11-18T23:18:00Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T23:17:29Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-3d87ec73400255919bd7eec6c594a3b4
|
tkcho
| 2023-11-19T07:02:41Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T07:02:11Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fe34d62cb4d88fc34f724917f75d7862
|
tkcho
| 2023-11-19T14:02:14Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T14:01:48Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fc4c2a953368838907d844aa60b3dd9b
|
tkcho
| 2023-11-20T08:27:13Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T08:26:47Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-95fcfc6f7c6591f19f1d1d4d01b81dfc
|
tkcho
| 2023-11-21T01:44:46Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T01:43:52Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3c00e8de54574b3a999fc05acbf4fe94
|
tkcho
| 2023-11-21T05:43:09Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T05:42:32Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-5e051e028f2d387f6e3f301889875bce
|
tkcho
| 2023-11-30T05:21:21Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T16:10:43Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-66ddb420e1ded386dd90807062ead2b5
|
tkcho
| 2023-11-21T16:52:51Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T16:52:23Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-da0c4083d24943de87080aea4e27ffb1
|
tkcho
| 2023-11-22T08:04:33Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T08:04:02Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-0d8a4d5b4b2246c559bd5d1de86d220e
|
tkcho
| 2023-11-22T08:15:58Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T08:15:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-03f7803cb8bf030a3d985cce5aae2945
|
tkcho
| 2023-11-24T02:45:40Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T02:45:13Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-eb137d2456a99dc82e24580f456a951e
|
tkcho
| 2023-11-24T10:41:09Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T10:40:39Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-74ee9ed88f4e6742f41dee48d95e0d65
|
tkcho
| 2023-11-24T13:17:49Z | 4,437 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T13:17:17Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f73bde0ee5839f7fe2c8480b83dbaff3
|
tkcho
| 2023-11-29T03:45:12Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T15:03:31Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-cc789c0b4f897dd886bd2b3fb9ee9cd2
|
tkcho
| 2023-11-12T15:40:46Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T15:40:02Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-834f13a029a37d9432d1e283ed97dbfe
|
tkcho
| 2023-11-16T03:29:49Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T03:29:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-034fc5963f56101c3a5b73ce49aa0ea7
|
tkcho
| 2023-11-17T01:03:51Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T01:03:23Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-772458473d34f84b70f6dde838fd030b
|
tkcho
| 2023-11-17T05:00:41Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T05:00:11Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1985e09e94234d928b21d5c6eb3315cf
|
tkcho
| 2023-11-17T13:37:33Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T13:37:04Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-eb67a0541e88abb685e89c3fdb47bdd8
|
tkcho
| 2023-11-18T01:49:31Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T01:49:03Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0c41ff8e8414e02ecdf62cfbcb6eda1c
|
tkcho
| 2023-11-18T02:45:48Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T02:45:16Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-dc3e4abc50b988be5a51a711ee3ab0ba
|
tkcho
| 2023-11-18T06:35:46Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T06:35:20Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b29e244fec72d9f9e7f93fdfe0f19387
|
tkcho
| 2023-11-18T17:33:57Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T17:33:30Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-81dff29b599c322b02688a2e5d75c046
|
tkcho
| 2023-11-19T00:12:21Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T00:11:52Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-7a2870024143fc4f2d465e6d402b8813
|
tkcho
| 2023-11-20T01:44:32Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T01:44:14Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0e1756c03672dd70dccbaab4bae5999b
|
tkcho
| 2023-11-20T07:53:22Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T07:52:45Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-28bbcf5bb5b2f5b41a8e3b08a053658b
|
tkcho
| 2023-11-21T01:51:00Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T01:50:10Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-9495d2e04b3c964d53ca1aa98e5fdbcd
|
tkcho
| 2023-11-21T05:01:39Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T05:01:11Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-6aa9e6d14b1ce34b5e9876271282cd11
|
tkcho
| 2023-11-21T13:48:42Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T13:48:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-a0c1d16dde103bc1c0591ed0395cdbb1
|
tkcho
| 2023-11-21T14:24:17Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T14:23:41Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-c6485f679f973eb5c3fbb14e2956229c
|
tkcho
| 2023-11-21T15:11:37Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T15:11:04Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d537434d424ffbc477de5867d3980e7e
|
tkcho
| 2023-11-21T15:17:30Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T15:17:01Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-c582f167aad4fee0c924df22b896c1bc
|
tkcho
| 2023-11-22T06:57:24Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T06:56:49Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cbfb83d2494090e85c7063448a3a974b
|
tkcho
| 2023-11-22T11:18:05Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T11:17:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-62294c01b4192f632eee843d0353752c
|
tkcho
| 2023-11-23T05:16:57Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T05:16:12Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-4e6f0a05cb1f4028a8279b9ade0401f6
|
tkcho
| 2023-11-23T10:52:48Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T10:52:19Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-2645da99adda8c0b547a9825a555e4a6
|
tkcho
| 2023-11-23T18:44:46Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T18:44:16Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-388e4221bbc17c8ab1530a8ae333ff48
|
tkcho
| 2023-11-23T22:56:31Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T22:56:04Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-bd89607c0706c3a105a70364ff08f784
|
tkcho
| 2023-11-24T06:02:19Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T06:01:55Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d7808de059cf9ac093ecdc439b439239
|
tkcho
| 2023-11-25T12:41:11Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T09:24:31Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-22f15effff9b10f6d306563f95a346f2
|
tkcho
| 2023-11-24T13:35:28Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T13:34:57Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-414ae7994f4c6d6f4e31c0f7270d3e21
|
tkcho
| 2023-11-24T15:15:56Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T15:15:29Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0ae8f76581e1a687e6ce522efe166425
|
tkcho
| 2023-11-25T02:49:06Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-25T02:48:39Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fe8d6dac1ced59c0089e6e9cf387b1bb
|
tkcho
| 2023-11-25T03:22:48Z | 4,436 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-25T03:22:20Z |
Entry not found
|
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harborwater/open-llama-3b-everything-v2
|
harborwater
| 2023-11-19T00:47:26Z | 4,435 | 1 |
transformers
|
[
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:totally-not-an-llm/EverythingLM-data-V2-sharegpt",
"license:apache-2.0",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-10-12T07:31:43Z |
---
license: apache-2.0
datasets:
- totally-not-an-llm/EverythingLM-data-V2-sharegpt
language:
- en
library_name: transformers
---
Trained on 3 epochs of the `totally-not-an-llm/EverythingLM-data-V2-sharegpt` dataset.
```
### HUMAN:
{prompt}
### RESPONSE:
<leave a newline for the model to answer>
```
note: Changed a few of the finetuning parameters this time around. I have no idea if its any good but Feel free to give it a try!
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_harborwater__open-llama-3b-everything-v2)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 36.29 |
| ARC (25-shot) | 42.83 |
| HellaSwag (10-shot) | 73.28 |
| MMLU (5-shot) | 26.87 |
| TruthfulQA (0-shot) | 37.26 |
| Winogrande (5-shot) | 66.61 |
| GSM8K (5-shot) | 1.59 |
| DROP (3-shot) | 5.61 |
|
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] |
tkcho/commerce-clf-kr-sku-brand-297258734b005caddd60b25605e0f27d
|
tkcho
| 2023-11-15T13:52:32Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T13:52:06Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-015306a464b6757738ba8d981e3c38c5
|
tkcho
| 2023-11-27T16:12:51Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T05:05:50Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0f2f63bddbbf213bc7728bdf865e5ef1
|
tkcho
| 2023-11-16T18:28:12Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T18:27:42Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-7d729e5db1170929650cf534f45e9919
|
tkcho
| 2023-11-16T20:16:46Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T20:16:10Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fdf78aeb77e01cb88ede64f59e2fcf1b
|
tkcho
| 2023-11-16T22:31:35Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T22:31:07Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-58bbab4619d3fd6ef3b550e609255a8c
|
tkcho
| 2023-11-17T00:09:33Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T00:09:05Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-9cc8d40d4d24bd5464255552c438feaf
|
tkcho
| 2023-11-17T00:42:03Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T00:41:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cc22f6b458a93a6086e6bf944cd0a73a
|
tkcho
| 2023-11-17T11:16:03Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T11:15:34Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f26c8e770ee03f3feb81097330bfc5c2
|
tkcho
| 2023-11-17T12:32:18Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T12:31:47Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-20e8a38026bffd9086cd7eb4051e600f
|
tkcho
| 2023-11-17T13:59:18Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T13:58:50Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-63cc08acecf2349fcdcfbe8d9e5d19f0
|
tkcho
| 2023-11-17T19:57:45Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T19:57:17Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-46df6d13517c35d82f4645b064c7b0b7
|
tkcho
| 2023-11-18T00:22:30Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T00:22:01Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f76eb71081406ba0fd3fcff8117d4940
|
tkcho
| 2023-11-18T01:06:08Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T01:05:41Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cba2e18ef7b356e75d32d4520230ccdc
|
tkcho
| 2023-11-19T05:11:06Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T05:10:41Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-13277384ae1044e0b087951b1e13ea6b
|
tkcho
| 2023-11-19T08:28:31Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T08:28:04Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-7388eb4c24b75647d2f9f1307ce17a45
|
tkcho
| 2023-11-20T01:23:00Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T01:22:38Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-669aa211673f06ac58d28124a938afb5
|
tkcho
| 2023-11-20T01:40:58Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T01:40:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-ee1d3f45e7c496e9076f37cbb912aa98
|
tkcho
| 2023-11-20T13:43:30Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T13:42:52Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-293bb869e487131361301f57e75f653e
|
tkcho
| 2023-11-20T14:27:55Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T14:27:28Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3f885be7ec88495843452331f13da223
|
tkcho
| 2023-11-21T06:42:35Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T06:42:01Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-c4ab0db97cee175afb93a9300a51d533
|
tkcho
| 2023-11-21T11:55:11Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T11:54:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-324d6fb5d1cf58b190dba569608bd073
|
tkcho
| 2023-11-21T16:41:02Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T16:40:35Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cf08cafee9de4421c1ddcaa4452e3b7a
|
tkcho
| 2023-11-22T09:40:16Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T09:39:43Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-919e2b7302d47b34e35bdbe727c27fdb
|
tkcho
| 2023-11-23T13:08:19Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T13:07:52Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-57fc91616037225202ae719abebe3cf8
|
tkcho
| 2023-11-24T02:51:46Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T02:51:06Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-9ddd8becfc102938917339c14fdf5b9d
|
tkcho
| 2023-11-24T08:43:14Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T08:42:42Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-bb16970a7cd1fcc7287808f1e9fae9f0
|
tkcho
| 2023-11-24T13:58:57Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T13:58:28Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-225fd39b868b4a50f3e0ef91b9a4cdae
|
tkcho
| 2023-11-24T15:04:09Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T15:03:41Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3bc81419a970ef60c70532143d93e0c5
|
tkcho
| 2023-11-24T15:57:12Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T15:56:43Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-6fc74c6005cf0bef18d453ef8268f551
|
tkcho
| 2023-11-24T16:15:08Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T16:14:34Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cdbc1a5756ef94430114cf301c4924dd
|
tkcho
| 2023-11-25T03:50:47Z | 4,435 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-25T03:50:11Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-467632172d73efdf94de975cf65da19c
|
tkcho
| 2023-11-25T23:14:33Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T16:39:17Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-5a91403150d3acbcd0d15b36d0b55305
|
tkcho
| 2023-11-27T14:15:54Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T17:17:33Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f3deb79cc7c3774061d3ef98cee46650
|
tkcho
| 2023-11-23T11:45:19Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-14T15:48:44Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-194c78fa514f690ee4c9a113e94bb533
|
tkcho
| 2023-11-15T10:13:37Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T10:13:06Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-3ab6d5e6877c03927355b6b425215596
|
tkcho
| 2023-11-16T23:58:42Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T23:58:14Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-98362b7f3dc27121a2c0d7aaaedbedef
|
tkcho
| 2023-11-17T18:52:22Z | 4,434 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T18:51:53Z |
Entry not found
|
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