Instructions to use andrealexroom/LexLLMv0.0.0.x.10.15a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andrealexroom/LexLLMv0.0.0.x.10.15a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="andrealexroom/LexLLMv0.0.0.x.10.15a")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("andrealexroom/LexLLMv0.0.0.x.10.15a") model = AutoModelForCausalLM.from_pretrained("andrealexroom/LexLLMv0.0.0.x.10.15a") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use andrealexroom/LexLLMv0.0.0.x.10.15a with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "andrealexroom/LexLLMv0.0.0.x.10.15a" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "andrealexroom/LexLLMv0.0.0.x.10.15a", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/andrealexroom/LexLLMv0.0.0.x.10.15a
- SGLang
How to use andrealexroom/LexLLMv0.0.0.x.10.15a 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 "andrealexroom/LexLLMv0.0.0.x.10.15a" \ --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": "andrealexroom/LexLLMv0.0.0.x.10.15a", "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 "andrealexroom/LexLLMv0.0.0.x.10.15a" \ --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": "andrealexroom/LexLLMv0.0.0.x.10.15a", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use andrealexroom/LexLLMv0.0.0.x.10.15a with Docker Model Runner:
docker model run hf.co/andrealexroom/LexLLMv0.0.0.x.10.15a
- Xet hash:
- e96e03c70cab2dff7c2fc184dadf72065ee0492ab10135b0b980a0b107474596
- Size of remote file:
- 29 GB
- SHA256:
- 999521f9141e055324574c19a214e858fe397293244cf9fb93ef6ad0d1e40fc4
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