Instructions to use typeform/distilroberta-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typeform/distilroberta-base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="typeform/distilroberta-base-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("typeform/distilroberta-base-v2") model = AutoModelForMaskedLM.from_pretrained("typeform/distilroberta-base-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from typeform/distilroberta-base-v2: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/typeform/distilroberta-base-v2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://typeform/distilroberta-base-v2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/typeform/distilroberta-base-v2/resolve/main/flax_model.msgpack
329 MB
- Xet hash:
- 7eadfe55c416a077c05b25e3e23804984590fe4f4924793d126b2f0da5623f4b
- Size of remote file:
- 329 MB
- SHA256:
- 4da82a2cd90eea052a0f4fe91e4edd3cebd337ab2439d147e6e68f712a2517d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.