Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ActiveYixiao/roberta-large-ToM4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ActiveYixiao/roberta-large-ToM4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ActiveYixiao/roberta-large-ToM4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ActiveYixiao/roberta-large-ToM4") model = AutoModelForSequenceClassification.from_pretrained("ActiveYixiao/roberta-large-ToM4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ActiveYixiao/roberta-large-ToM4: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/ActiveYixiao/roberta-large-ToM4/resolve/main/training_args.bin
- Command line
-
hf download hf://ActiveYixiao/roberta-large-ToM4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ActiveYixiao/roberta-large-ToM4/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 0de8e46e0e1d4a89209976a4ef307541cfc9e9f0d39e2a270bbd1d8237d5b1fc
- Size of remote file:
- 5.78 kB
- SHA256:
- 79c5eb0f53202fda65dbaf6bc0b6b8142e3a646fedbf67f6529e3efacb3e6378
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