Instructions to use improz4/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use improz4/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="improz4/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("improz4/model") model = AutoModelForMaskedLM.from_pretrained("improz4/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from improz4/model: direct link, hf CLI and curl.
- Browser
- Download file 30.3 MB
-
https://huggingface.co/improz4/model/resolve/c5137cedc97276009f8abcb1d8d73c8c19afabcc/pytorch_model.bin
- Command line
-
hf download hf://improz4/model@c5137cedc97276009f8abcb1d8d73c8c19afabcc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/improz4/model/resolve/c5137cedc97276009f8abcb1d8d73c8c19afabcc/pytorch_model.bin
30.3 MB
- Xet hash:
- ab3860ab9eb4aa80d48a91f4f9360593808cbfbecd1854d689e872d736a0ff57
- Size of remote file:
- 30.3 MB
- SHA256:
- 097f18abbf5c9f3d96a4b743cd5ffded5cb09929718801dd283538f8911f75c2
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