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/eb18d24f3d7cbebb100ae2b38b1066bd96c8a227/training_args.bin
- Command line
-
hf download hf://RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified@eb18d24f3d7cbebb100ae2b38b1066bd96c8a227/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RajuEEE/RewardModelSmallerQuestionWithTwoLabelsLengthJustified/resolve/eb18d24f3d7cbebb100ae2b38b1066bd96c8a227/training_args.bin
4.66 kB
- Xet hash:
- 947042ad9dbd16367cfdf6a895f49ff24a4a08a2af44e3cdcebd2a943067a3f9
- Size of remote file:
- 4.66 kB
- SHA256:
- 7961b4cca313a7059414d8bd3696c1b6c9245b262205189fd0b4702f26863b49
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