Instructions to use Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1")
model = AutoModelForCausalLM.from_pretrained("Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1

SGLang

How to use Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1 with Docker Model Runner:
```
docker model run hf.co/Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1
```

Tlamatini Papalotl: The Wisdom-Butterfly: V0.1 Coder (Programming Assistance)

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
- sources:
  - layer_range: [0, 16]
    model: codellama/CodeLlama-7b-Instruct-hf
- sources:
  - layer_range: [2, 22]
    model: Phind/Phind-CodeLlama-34B-Python-v1
- sources:
  - layer_range: [8, 26]
    model: codellama/CodeLlama-7b-Python-hf
- sources:
  - layer_range: [10, 30]
    model: Phind/Phind-CodeLlama-34B-v2
- sources:
  - layer_range: [14, 32]
    model: Phind/Phind-CodeLlama-34B-v2
merge_method: passthrough
dtype: float16

Downloads last month: 6

Safetensors

Model size

47B params

Tensor type

F16

Model tree for Solshine/Tlamatini-Papalotl-Wisdom-Butterfly-CodeLlama-v0-1

Phind/Phind-CodeLlama-34B-Python-v1

Phind/Phind-CodeLlama-34B-v2

codellama/CodeLlama-7b-Instruct-hf

codellama/CodeLlama-7b-Python-hf

Merge model

this model