Instructions to use Plaban81/codegen-int4-GPTQ-python-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Plaban81/codegen-int4-GPTQ-python-code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Plaban81/codegen-int4-GPTQ-python-code")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Plaban81/codegen-int4-GPTQ-python-code") model = AutoModelForCausalLM.from_pretrained("Plaban81/codegen-int4-GPTQ-python-code") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Plaban81/codegen-int4-GPTQ-python-code with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Plaban81/codegen-int4-GPTQ-python-code" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Plaban81/codegen-int4-GPTQ-python-code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Plaban81/codegen-int4-GPTQ-python-code
- SGLang
How to use Plaban81/codegen-int4-GPTQ-python-code 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 "Plaban81/codegen-int4-GPTQ-python-code" \ --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": "Plaban81/codegen-int4-GPTQ-python-code", "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 "Plaban81/codegen-int4-GPTQ-python-code" \ --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": "Plaban81/codegen-int4-GPTQ-python-code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Plaban81/codegen-int4-GPTQ-python-code with Docker Model Runner:
docker model run hf.co/Plaban81/codegen-int4-GPTQ-python-code
- Xet hash:
- 31abff28870c9e8ce49f002cc7600a2f5cd17e85074670d148db1bbe7fa10c4c
- Size of remote file:
- 3.9 GB
- SHA256:
- a2005b86b4a899ccd54d4a5f651294f2c3e3372eacc7854a5ca62aff842234e1
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