Instructions to use sunilsai/new_cache with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunilsai/new_cache with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="sunilsai/new_cache")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("sunilsai/new_cache") model = AutoModelForImageTextToText.from_pretrained("sunilsai/new_cache") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use sunilsai/new_cache with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sunilsai/new_cache" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sunilsai/new_cache", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sunilsai/new_cache
- SGLang
How to use sunilsai/new_cache 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 "sunilsai/new_cache" \ --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": "sunilsai/new_cache", "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 "sunilsai/new_cache" \ --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": "sunilsai/new_cache", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sunilsai/new_cache with Docker Model Runner:
docker model run hf.co/sunilsai/new_cache
- Xet hash:
- 48913598eaa2f9e5e51bf89549d052cfe798bd55de35b40f3661ac0bc07d0c30
- Size of remote file:
- 4.28 kB
- SHA256:
- ca64259772394d9be410cd9bab4d8d083ab74954a5a464968576285c2659acac
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