Instructions to use hagara/roberta-large-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hagara/roberta-large-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hagara/roberta-large-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hagara/roberta-large-2") model = AutoModelForSequenceClassification.from_pretrained("hagara/roberta-large-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hagara/roberta-large-2: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/hagara/roberta-large-2/resolve/main/training_args.bin
- Command line
-
hf download hf://hagara/roberta-large-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hagara/roberta-large-2/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- a9231b222025f46a0668c4628eada3a4a5acd67b4175999be8759d40618a19fd
- Size of remote file:
- 4.09 kB
- SHA256:
- 70814573f0ff7a3c2b42f68b22ed41407e565e313d4d0e8b6607750f590bbaa1
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