Instructions to use flax-community/roberta-hindi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/roberta-hindi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/roberta-hindi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-hindi") model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-hindi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from flax-community/roberta-hindi: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/flax-community/roberta-hindi/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://flax-community/roberta-hindi/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax-community/roberta-hindi/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 84fcd5b299170fe1d741ced95818b3809168d0e328b60c186d95fb727e0131cd
- Size of remote file:
- 499 MB
- SHA256:
- 904705cb48bfd59a5d3aed1f30746844238567349459d7e3e09aca20dbfb1e35
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