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 pytorch_model.bin from mahaamami/distilroberta-base-model: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/mahaamami/distilroberta-base-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mahaamami/distilroberta-base-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mahaamami/distilroberta-base-model/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- e353598b5df0e1640c5871a89f7f5690b155c4215aca8ebe8962bc8dec928a50
- Size of remote file:
- 329 MB
- SHA256:
- 9c3369066b0dbde1182795b8799c83341c18a328b63fc348013702ae5583c514
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