Instructions to use Open-Orca/Mistral-7B-SlimOrca with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Open-Orca/Mistral-7B-SlimOrca with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Open-Orca/Mistral-7B-SlimOrca")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Open-Orca/Mistral-7B-SlimOrca") model = AutoModelForCausalLM.from_pretrained("Open-Orca/Mistral-7B-SlimOrca", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Open-Orca/Mistral-7B-SlimOrca with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Open-Orca/Mistral-7B-SlimOrca" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Open-Orca/Mistral-7B-SlimOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Open-Orca/Mistral-7B-SlimOrca
- SGLang
How to use Open-Orca/Mistral-7B-SlimOrca 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 "Open-Orca/Mistral-7B-SlimOrca" \ --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": "Open-Orca/Mistral-7B-SlimOrca", "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 "Open-Orca/Mistral-7B-SlimOrca" \ --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": "Open-Orca/Mistral-7B-SlimOrca", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Open-Orca/Mistral-7B-SlimOrca with Docker Model Runner:
docker model run hf.co/Open-Orca/Mistral-7B-SlimOrca
Commit History
-
remove the leaderboard results from the open-llm-leaderboard pr bot because they dont look good
d36453f
-
Adding Evaluation Results (#2)
- Adding Evaluation Results (0eaa3adaac7103a6a58b05a0610308f7a35ae652) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>e10c598
-
Update README.md
da46163
-
Update README.md
5be510b
-
slimorca dataset citation
54e9364
-
Update README.md
c1ac646 -
Update README.md
95daa42 -
Create README.md
b40ee77
-
ep4
a9744d8 -
ep3
19fb7de -
ep2
4951f14
-
ep1
b821748 -
initial commit
3af80f5