Instructions to use llmware/bling-tiny-llama-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/bling-tiny-llama-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="llmware/bling-tiny-llama-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("llmware/bling-tiny-llama-onnx") model = AutoModelForCausalLM.from_pretrained("llmware/bling-tiny-llama-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use llmware/bling-tiny-llama-onnx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "llmware/bling-tiny-llama-onnx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "llmware/bling-tiny-llama-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/llmware/bling-tiny-llama-onnx
- SGLang
How to use llmware/bling-tiny-llama-onnx 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 "llmware/bling-tiny-llama-onnx" \ --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": "llmware/bling-tiny-llama-onnx", "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 "llmware/bling-tiny-llama-onnx" \ --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": "llmware/bling-tiny-llama-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use llmware/bling-tiny-llama-onnx with Docker Model Runner:
docker model run hf.co/llmware/bling-tiny-llama-onnx
Commit History
-
Update README.md
Verified signature467189b
-
Update README.md
Verified signaturee3ba994 -
Upload hash_record_sha256.json
Verified signature04890cd -
Update README.md
Verified signature5c234aa -
Upload README.md
Verified signature302d3c0
-
Update README.md
Verified signaturec3a0616 -
Update config.json
Verified signature128a069 -
Update README.md
Verified signature449ac8b -
Upload config.json
Verified signaturebce4718 -
Upload README.md
Verified signaturee1509c1
-
Upload model.onnx.data
Verified signature6b8ab77 -
Upload 6 files
Verified signature434b1b4 -
initial commit
Verified signature04945af