Instructions to use mahaamami/distilroberta-base-model-transcript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahaamami/distilroberta-base-model-transcript with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mahaamami/distilroberta-base-model-transcript")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mahaamami/distilroberta-base-model-transcript") model = AutoModelForMaskedLM.from_pretrained("mahaamami/distilroberta-base-model-transcript", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mahaamami/distilroberta-base-model-transcript: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/mahaamami/distilroberta-base-model-transcript/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://mahaamami/distilroberta-base-model-transcript@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mahaamami/distilroberta-base-model-transcript/resolve/refs%2Fpr%2F1/pytorch_model.bin
329 MB
- Xet hash:
- b8d19bfcd97f7e92b12b0d7db398271137215f70e3255406adeab051ed73f9a5
- Size of remote file:
- 329 MB
- SHA256:
- 40d2606f9c7dd0fde71e58e9808db270d30e30c0759bf133dbd8bbff90847fc8
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