Instructions to use subbareddyiiit/RobertaNLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use subbareddyiiit/RobertaNLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="subbareddyiiit/RobertaNLP")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("subbareddyiiit/RobertaNLP") model = AutoModelForMaskedLM.from_pretrained("subbareddyiiit/RobertaNLP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from subbareddyiiit/RobertaNLP: direct link, hf CLI and curl.
- Browser
- Download file 353 MB
-
https://huggingface.co/subbareddyiiit/RobertaNLP/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://subbareddyiiit/RobertaNLP/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/subbareddyiiit/RobertaNLP/resolve/main/flax_model.msgpack
353 MB
- Xet hash:
- f154910bb372520589b82501d494d18aacebce40a9128e1d1c86e364220285b7
- Size of remote file:
- 353 MB
- SHA256:
- 5c812533b46d9c3119d8c2b28177012b24bddcc717b25faab3670e5a61483425
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