Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified") model = AutoModelForSequenceClassification.from_pretrained("RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/resolve/main/training_args.bin
- Command line
-
hf download hf://RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- a7465a68b915a8cfb8c5de07a37a8166982da786d1adc64ef1970be27c0b6fe7
- Size of remote file:
- 4.66 kB
- SHA256:
- 788e73bbfa6715e6c76bf79bc2126f5ae14fec447cba5b690674fcb727bb646c
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