Instructions to use m3rg-iitd/matscibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3rg-iitd/matscibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="m3rg-iitd/matscibert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("m3rg-iitd/matscibert") model = AutoModelForMaskedLM.from_pretrained("m3rg-iitd/matscibert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from m3rg-iitd/matscibert: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/m3rg-iitd/matscibert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://m3rg-iitd/matscibert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/m3rg-iitd/matscibert/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 08575ef2c9133b130a72a24309272e756f5f380bbf876ab9de0dc2c112fbada3
- Size of remote file:
- 440 MB
- SHA256:
- b9c8f83a7ed9840a6f1fb18619210b91bec55a2260c68dba921d53daf3aa769e
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