Instructions to use TheBloke/orca_mini_v3_13B-GGML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/orca_mini_v3_13B-GGML with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/orca_mini_v3_13B-GGML")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheBloke/orca_mini_v3_13B-GGML", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TheBloke/orca_mini_v3_13B-GGML with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/orca_mini_v3_13B-GGML" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/orca_mini_v3_13B-GGML", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/orca_mini_v3_13B-GGML
- SGLang
How to use TheBloke/orca_mini_v3_13B-GGML 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 "TheBloke/orca_mini_v3_13B-GGML" \ --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": "TheBloke/orca_mini_v3_13B-GGML", "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 "TheBloke/orca_mini_v3_13B-GGML" \ --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": "TheBloke/orca_mini_v3_13B-GGML", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/orca_mini_v3_13B-GGML with Docker Model Runner:
docker model run hf.co/TheBloke/orca_mini_v3_13B-GGML
Download orca_mini_v3_13b.ggmlv3.q2_K.bin from TheBloke/orca_mini_v3_13B-GGML: direct link, hf CLI and curl.
- Browser
- Download file 5.51 GB
-
https://huggingface.co/TheBloke/orca_mini_v3_13B-GGML/resolve/main/orca_mini_v3_13b.ggmlv3.q2_K.bin
- Command line
-
hf download hf://TheBloke/orca_mini_v3_13B-GGML/orca_mini_v3_13b.ggmlv3.q2_K.bin
-
curl -L -o orca_mini_v3_13b.ggmlv3.q2_K.bin https://huggingface.co/TheBloke/orca_mini_v3_13B-GGML/resolve/main/orca_mini_v3_13b.ggmlv3.q2_K.bin
5.51 GB
- Xet hash:
- 30bcbf36ac71496c05bbe96643905624b5a39b65f663ee3c710b7693fb40b89c
- Size of remote file:
- 5.51 GB
- SHA256:
- 9490fd5d47af466e3a5cdfd7846a4b7094f8483a8d8c441e57c0a34e51c9f4b2
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