Text Generation
Transformers
PyTorch
Safetensors
English
llama
Eval Results (legacy)
text-generation-inference
Instructions to use pankajmathur/orca_mini_v3_7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pankajmathur/orca_mini_v3_7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pankajmathur/orca_mini_v3_7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pankajmathur/orca_mini_v3_7b") model = AutoModelForCausalLM.from_pretrained("pankajmathur/orca_mini_v3_7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pankajmathur/orca_mini_v3_7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pankajmathur/orca_mini_v3_7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pankajmathur/orca_mini_v3_7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pankajmathur/orca_mini_v3_7b
- SGLang
How to use pankajmathur/orca_mini_v3_7b 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 "pankajmathur/orca_mini_v3_7b" \ --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": "pankajmathur/orca_mini_v3_7b", "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 "pankajmathur/orca_mini_v3_7b" \ --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": "pankajmathur/orca_mini_v3_7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pankajmathur/orca_mini_v3_7b with Docker Model Runner:
docker model run hf.co/pankajmathur/orca_mini_v3_7b
Commit History
-
Adding `safetensors` variant of this model (#8)
Verified signature- Adding `safetensors` variant of this model (b5a134ce3d425ed783b8009df178f9852c776f59) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>0cbb2b5
-
Adding Evaluation Results (#7)
Verified signature- Adding Evaluation Results (f94e1587bb6a052a0d9b1bf2a3d6efcd0c63529f) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>fe1953e
-
Adding Evaluation Results (#6)
Verified signature- Adding Evaluation Results (e711d33a4a7a8385772983dbcc72d2d1ff273446) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>6252eb7
-
Adding Evaluation Results (#5)
- Adding Evaluation Results (2d3bbba235e155309c4b1c55494f86958cd3c9bc) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>7b2f814
-
Update README.md
f9849ea
-
Update README.md
21ef508 -
Upload orca_minis_small.jpeg
373e60f -
Delete orca_minis.jpeg
31b5c70 -
Upload orca_minis.jpeg
8b2c889
-
Update README.md
0419bd9 -
Update README.md
d5fe5f3
-
Update README.md
a1583d2 -
Update README.md
05600c0
-
Update README.md
d1fa68f
-
Update README.md
feb746d -
Update README.md
c395ffb -
Update README.md
54aaffa -
Update README.md
33edc1c -
Create README.md
bb7ae54 -
Initial Commit
9a8268e
-
initial commit
93e2e49