Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Rasmy/roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rasmy/roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rasmy/roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rasmy/roberta") model = AutoModelForSequenceClassification.from_pretrained("Rasmy/roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Rasmy/roberta: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/Rasmy/roberta/resolve/main/training_args.bin
- Command line
-
hf download hf://Rasmy/roberta/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Rasmy/roberta/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 78a6ce7c4ba35ef7d7767649c8a87185358e4057929fb1cece5c5d7921aa5038
- Size of remote file:
- 5.3 kB
- SHA256:
- a53d5b9cc911bf550cabbcc424d3b8c89ba984b06093e5bad640b4feec784241
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