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 optimizer.pt from gargam/roberta-base-crest: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/gargam/roberta-base-crest/resolve/main/optimizer.pt
- Command line
-
hf download hf://gargam/roberta-base-crest/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/gargam/roberta-base-crest/resolve/main/optimizer.pt
997 MB
- Xet hash:
- 75ed4e046c9bf4ecff3da2d95b5de88d26aca1655532a3df299fd3a85c9605d3
- Size of remote file:
- 997 MB
- SHA256:
- 336454b0a1743d9d3c053f2c65bca60aa6d81f3993fa36364469bc27c4c16505
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