Instructions to use ulkaa/CodeLlama-7b-hf-sym_int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ulkaa/CodeLlama-7b-hf-sym_int8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ulkaa/CodeLlama-7b-hf-sym_int8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ulkaa/CodeLlama-7b-hf-sym_int8") model = AutoModelForCausalLM.from_pretrained("ulkaa/CodeLlama-7b-hf-sym_int8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ulkaa/CodeLlama-7b-hf-sym_int8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ulkaa/CodeLlama-7b-hf-sym_int8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ulkaa/CodeLlama-7b-hf-sym_int8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ulkaa/CodeLlama-7b-hf-sym_int8
- SGLang
How to use ulkaa/CodeLlama-7b-hf-sym_int8 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 "ulkaa/CodeLlama-7b-hf-sym_int8" \ --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": "ulkaa/CodeLlama-7b-hf-sym_int8", "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 "ulkaa/CodeLlama-7b-hf-sym_int8" \ --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": "ulkaa/CodeLlama-7b-hf-sym_int8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ulkaa/CodeLlama-7b-hf-sym_int8 with Docker Model Runner:
docker model run hf.co/ulkaa/CodeLlama-7b-hf-sym_int8
Commit History
-
Upload pytorch_model-00002-of-00002.bin with huggingface_hub
Verified signaturef01e522 -
Upload load_keys.json with huggingface_hub
Verified signature732e368 -
Upload tokenizer_config.json with huggingface_hub
Verified signature9c6b987 -
Upload pytorch_model.bin.index.json with huggingface_hub
Verified signature4ff6672 -
Upload generation_config.json with huggingface_hub
Verified signatureac969bf -
Upload tokenizer.model with huggingface_hub
Verified signaturee998543 -
Upload tokenizer.json with huggingface_hub
Verified signature37dd01a -
Upload config.json with huggingface_hub
Verified signature4bea829 -
Upload pytorch_model-00001-of-00002.bin with huggingface_hub
Verified signaturedd5ac53 -
Upload special_tokens_map.json with huggingface_hub
Verified signature9c8ec9f -
initial commit
Verified signature1214563