Instructions to use switlydev/MyMiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use switlydev/MyMiniLM with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("switlydev/MyMiniLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download model.safetensors from switlydev/MyMiniLM: direct link, hf CLI and curl.
- Browser
- Download file 3.09 GB
-
https://huggingface.co/switlydev/MyMiniLM/resolve/main/model.safetensors
- Command line
-
hf download hf://switlydev/MyMiniLM/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/switlydev/MyMiniLM/resolve/main/model.safetensors
3.09 GB
- Xet hash:
- ce3dfb7bcfdebd3e499f1900c1a349e32aa8181b7230c8d7df6443c2bfb370b9
- Size of remote file:
- 3.09 GB
- SHA256:
- 6c8488f92181241436672a39b1e0c921caa95b8367e92c42575582b6a5b4af68
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