Instructions to use 0639osama/newmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0639osama/newmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="0639osama/newmodel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("0639osama/newmodel") model = AutoModelForCausalLM.from_pretrained("0639osama/newmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 0639osama/newmodel with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "0639osama/newmodel" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "0639osama/newmodel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/0639osama/newmodel
- SGLang
How to use 0639osama/newmodel 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 "0639osama/newmodel" \ --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": "0639osama/newmodel", "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 "0639osama/newmodel" \ --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": "0639osama/newmodel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 0639osama/newmodel with Docker Model Runner:
docker model run hf.co/0639osama/newmodel
Download pytorch_model.bin from 0639osama/newmodel: direct link, hf CLI and curl.
- Browser
- Download file 1.4 GB
-
https://huggingface.co/0639osama/newmodel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://0639osama/newmodel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/0639osama/newmodel/resolve/main/pytorch_model.bin
1.4 GB
- Xet hash:
- 161264a5ac9cad222ecdafa602aa44ca4e0660e797937c68dcbe43a10a482750
- Size of remote file:
- 1.4 GB
- SHA256:
- b838921fe3afeeb84414fd73170d5a57c4c751cc9a6a3342d7164d802e561c9a
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