Instructions to use mahaamami/distilroberta-base-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahaamami/distilroberta-base-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mahaamami/distilroberta-base-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mahaamami/distilroberta-base-model") model = AutoModelForMaskedLM.from_pretrained("mahaamami/distilroberta-base-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mahaamami/distilroberta-base-model: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/mahaamami/distilroberta-base-model/resolve/main/training_args.bin
- Command line
-
hf download hf://mahaamami/distilroberta-base-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mahaamami/distilroberta-base-model/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- cae17beffa06e4e5e739d47814ce8a5531472250ed0fbe62fd4f7b2cde60732c
- Size of remote file:
- 2.93 kB
- SHA256:
- f09bef3afae3c1032ce3ae3e595bd0bba4294ea501bed6ceb218f3de8094b3de
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