Instructions to use ArushBuilds/Pragya-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArushBuilds/Pragya-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ArushBuilds/Pragya-Preview")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArushBuilds/Pragya-Preview", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ArushBuilds/Pragya-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ArushBuilds/Pragya-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ArushBuilds/Pragya-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ArushBuilds/Pragya-Preview
- SGLang
How to use ArushBuilds/Pragya-Preview 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 "ArushBuilds/Pragya-Preview" \ --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": "ArushBuilds/Pragya-Preview", "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 "ArushBuilds/Pragya-Preview" \ --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": "ArushBuilds/Pragya-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ArushBuilds/Pragya-Preview with Docker Model Runner:
docker model run hf.co/ArushBuilds/Pragya-Preview
Download model.onnx from ArushBuilds/Pragya-Preview: direct link, hf CLI and curl.
- Browser
- Download file 36.4 MB
-
https://huggingface.co/ArushBuilds/Pragya-Preview/resolve/main/model.onnx
- Command line
-
hf download hf://ArushBuilds/Pragya-Preview/model.onnx
-
curl -L -o model.onnx https://huggingface.co/ArushBuilds/Pragya-Preview/resolve/main/model.onnx
36.4 MB
- Xet hash:
- 34b091dad584edfca80ff3b91b2f8383348c8e2c344b279a046b820eb920ea28
- Size of remote file:
- 36.4 MB
- SHA256:
- e513d1cf313a4c399e241fc96a487b0f7dc47580c80605c5d0bccf41f3d68b4c
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