Feature Extraction
sentence-transformers
PyTorch
ONNX
Safetensors
Transformers
Transformers.js
English
bert
fill-mask
sentence-similarity
mteb
custom_code
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use jinaai/jina-embeddings-v2-base-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jinaai/jina-embeddings-v2-base-code with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jinaai/jina-embeddings-v2-base-code", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use jinaai/jina-embeddings-v2-base-code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jinaai/jina-embeddings-v2-base-code", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jinaai/jina-embeddings-v2-base-code", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("jinaai/jina-embeddings-v2-base-code", trust_remote_code=True, device_map="auto") - Transformers.js
How to use jinaai/jina-embeddings-v2-base-code with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'jinaai/jina-embeddings-v2-base-code'); - Notebooks
- Google Colab
- Kaggle
Upload 6 files
Browse files- config (1).json +37 -0
- generation_config (1).json +5 -0
- special_tokens_map (2).json +15 -0
- tokenizer.json +0 -0
- tokenizer_config (2).json +22 -0
- vocab.json +0 -0
config (1).json
ADDED
|
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "jinaai/jina-bert-v2-de-61k",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"JinaBertForMaskedLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"attn_implementation": "torch",
|
| 8 |
+
"auto_map": {
|
| 9 |
+
"AutoConfig": "jinaai/jina-bert-implementation--configuration_bert.JinaBertConfig",
|
| 10 |
+
"AutoModel": "jinaai/jina-bert-implementation--modeling_bert.JinaBertModel",
|
| 11 |
+
"AutoModelForMaskedLM": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForMaskedLM",
|
| 12 |
+
"AutoModelForQuestionAnswering": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForQuestionAnswering",
|
| 13 |
+
"AutoModelForSequenceClassification": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForSequenceClassification",
|
| 14 |
+
"AutoModelForTokenClassification": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForTokenClassification"
|
| 15 |
+
},
|
| 16 |
+
"classifier_dropout": null,
|
| 17 |
+
"emb_pooler": "mean",
|
| 18 |
+
"feed_forward_type": "geglu",
|
| 19 |
+
"gradient_checkpointing": false,
|
| 20 |
+
"hidden_act": "gelu",
|
| 21 |
+
"hidden_dropout_prob": 0.1,
|
| 22 |
+
"hidden_size": 768,
|
| 23 |
+
"initializer_range": 0.02,
|
| 24 |
+
"intermediate_size": 3072,
|
| 25 |
+
"layer_norm_eps": 1e-12,
|
| 26 |
+
"max_position_embeddings": 8192,
|
| 27 |
+
"model_type": "bert",
|
| 28 |
+
"num_attention_heads": 12,
|
| 29 |
+
"num_hidden_layers": 12,
|
| 30 |
+
"pad_token_id": 0,
|
| 31 |
+
"position_embedding_type": "alibi",
|
| 32 |
+
"torch_dtype": "float16",
|
| 33 |
+
"transformers_version": "4.31.0",
|
| 34 |
+
"type_vocab_size": 2,
|
| 35 |
+
"use_cache": true,
|
| 36 |
+
"vocab_size": 61056
|
| 37 |
+
}
|
generation_config (1).json
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"pad_token_id": 0,
|
| 4 |
+
"transformers_version": "4.31.0"
|
| 5 |
+
}
|
special_tokens_map (2).json
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": "<s>",
|
| 3 |
+
"cls_token": "<s>",
|
| 4 |
+
"eos_token": "</s>",
|
| 5 |
+
"mask_token": {
|
| 6 |
+
"content": "<mask>",
|
| 7 |
+
"lstrip": true,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false
|
| 11 |
+
},
|
| 12 |
+
"pad_token": "<pad>",
|
| 13 |
+
"sep_token": "</s>",
|
| 14 |
+
"unk_token": "<unk>"
|
| 15 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config (2).json
ADDED
|
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"bos_token": "<s>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"cls_token": "<s>",
|
| 6 |
+
"eos_token": "</s>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"mask_token": {
|
| 9 |
+
"__type": "AddedToken",
|
| 10 |
+
"content": "<mask>",
|
| 11 |
+
"lstrip": true,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"model_max_length": 512,
|
| 17 |
+
"pad_token": "<pad>",
|
| 18 |
+
"sep_token": "</s>",
|
| 19 |
+
"tokenizer_class": "RobertaTokenizer",
|
| 20 |
+
"trim_offsets": true,
|
| 21 |
+
"unk_token": "<unk>"
|
| 22 |
+
}
|
vocab.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|