Instructions to use simran-kh/muril-cased-temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simran-kh/muril-cased-temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="simran-kh/muril-cased-temp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("simran-kh/muril-cased-temp") model = AutoModel.from_pretrained("simran-kh/muril-cased-temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from simran-kh/muril-cased-temp: direct link, hf CLI and curl.
- Browser
- Download file 950 MB
-
https://huggingface.co/simran-kh/muril-cased-temp/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://simran-kh/muril-cased-temp/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/simran-kh/muril-cased-temp/resolve/main/flax_model.msgpack
950 MB
- Xet hash:
- 216fa7dbdf5adb811a34b5d757ae79d8c1630e1a30766c0887cdf18797146ec5
- Size of remote file:
- 950 MB
- SHA256:
- 74b7f3a15e095b02bad73b4f9cd14e1be81540b68000ddee79f41b3f51812759
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