Instructions to use gargam/roberta-base-crest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gargam/roberta-base-crest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gargam/roberta-base-crest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gargam/roberta-base-crest") model = AutoModelForSequenceClassification.from_pretrained("gargam/roberta-base-crest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gargam/roberta-base-crest: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/gargam/roberta-base-crest/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gargam/roberta-base-crest/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gargam/roberta-base-crest/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- dd9109355db8f07d26be48195ae6aed4690577645867ea71c6777e22492a807b
- Size of remote file:
- 501 MB
- SHA256:
- 801b682d57c37f474e28a2111ab78d1a8c9feecf594d4962d9d3d43cf631197b
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