Text Generation
Transformers
Safetensors
code
llama
llama-2
custom_code
text-generation-inference
4-bit precision
gptq
Instructions to use TheBloke/CodeLlama-7B-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/CodeLlama-7B-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/CodeLlama-7B-GPTQ", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TheBloke/CodeLlama-7B-GPTQ", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("TheBloke/CodeLlama-7B-GPTQ", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TheBloke/CodeLlama-7B-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/CodeLlama-7B-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/CodeLlama-7B-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/CodeLlama-7B-GPTQ
- SGLang
How to use TheBloke/CodeLlama-7B-GPTQ 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 "TheBloke/CodeLlama-7B-GPTQ" \ --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": "TheBloke/CodeLlama-7B-GPTQ", "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 "TheBloke/CodeLlama-7B-GPTQ" \ --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": "TheBloke/CodeLlama-7B-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/CodeLlama-7B-GPTQ with Docker Model Runner:
docker model run hf.co/TheBloke/CodeLlama-7B-GPTQ
Commit History
-
Update base_model formatting
1c710a5
-
Upload README.md
8515be0 -
Upload README.md
5c98ade
-
Upload README.md
a3090d1 -
Upload README.md
fd8f666
-
Initial GPTQ model commit
304ae7d -
Initial GPTQ model commit
bcb6f80 -
Initial GPTQ model commit
630d3b9 -
Initial GPTQ model commit
378c2a9 -
Initial GPTQ model commit
a6ab4af
-
Add pad_token_id to config.json
d89e95a -
Fix generation_config.json
bda7e92 -
Initial GPTQ model commit
d2dc231 -
Initial GPTQ model commit
5e08bb4 -
Initial GPTQ model commit
245154d -
Initial GPTQ model commit
7e440be -
Initial GPTQ model commit
c588ac3 -
Initial GPTQ model commit
d58f201 -
Initial GPTQ model commit
14fdc37 -
Initial GPTQ model commit
c5e5bdf -
Initial GPTQ model commit
267de57 -
Initial GPTQ model commit
497cfca -
Initial GPTQ model commit
87018d2 -
Initial GPTQ model commit
049eb09 -
Initial GPTQ model commit
a2d788d -
Initial GPTQ model commit
9d7296a -
Initial GPTQ model commit
f23d3e9 -
Initial GPTQ model commit
367a3f4
-
initial commit
306a1f7