Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified") model = AutoModelForSequenceClassification.from_pretrained("SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/resolve/main/training_args.bin
- Command line
-
hf download hf://SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SudiptoPramanik/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 87234e23e62a5ebc76933969e629f1eb2b4910daffb5df31751eed06c045b98f
- Size of remote file:
- 4.66 kB
- SHA256:
- d62dbe25d65322a60e61f30a77228e0a9971a13a3d8a0bc906eea153d6b820f9
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