Instructions to use matchaaaaa/Misted-Toppy-11B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matchaaaaa/Misted-Toppy-11B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="matchaaaaa/Misted-Toppy-11B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("matchaaaaa/Misted-Toppy-11B") model = AutoModelForCausalLM.from_pretrained("matchaaaaa/Misted-Toppy-11B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use matchaaaaa/Misted-Toppy-11B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "matchaaaaa/Misted-Toppy-11B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "matchaaaaa/Misted-Toppy-11B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/matchaaaaa/Misted-Toppy-11B
- SGLang
How to use matchaaaaa/Misted-Toppy-11B 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 "matchaaaaa/Misted-Toppy-11B" \ --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": "matchaaaaa/Misted-Toppy-11B", "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 "matchaaaaa/Misted-Toppy-11B" \ --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": "matchaaaaa/Misted-Toppy-11B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use matchaaaaa/Misted-Toppy-11B with Docker Model Runner:
docker model run hf.co/matchaaaaa/Misted-Toppy-11B
Ctrl+K
- 1.52 kB
- 486 Bytes
- 660 Bytes
- 212 Bytes
- 961 MB xet
- 906 MB xet
- 990 MB xet
- 998 MB xet
- 982 MB xet
- 923 MB xet
- 990 MB xet
- 990 MB xet
- 990 MB xet
- 990 MB xet
- 956 MB xet
- 990 MB xet
- 990 MB xet
- 990 MB xet
- 956 MB xet
- 990 MB xet
- 998 MB xet
- 948 MB xet
- 990 MB xet
- 990 MB xet
- 990 MB xet
- 956 MB xet
- 34.1 kB
- 437 Bytes
- 1.8 MB
- 493 kB xet
- 1.01 kB