Instructions to use rifkat/uztext-3Gb-BPE-Roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rifkat/uztext-3Gb-BPE-Roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rifkat/uztext-3Gb-BPE-Roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rifkat/uztext-3Gb-BPE-Roberta") model = AutoModelForMaskedLM.from_pretrained("rifkat/uztext-3Gb-BPE-Roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rifkat/uztext-3Gb-BPE-Roberta: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/rifkat/uztext-3Gb-BPE-Roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://rifkat/uztext-3Gb-BPE-Roberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rifkat/uztext-3Gb-BPE-Roberta/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- 40f4868be69447ca6bef9bf565d7bc7fb941b863034e2b213dc6cc8d855052b2
- Size of remote file:
- 2.48 kB
- SHA256:
- 377282aa8b437dd2b76567feb2cd3ad250ec267cbfa289e224e37422fd636b92
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