Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use RajuEEE/RewardModel_RobertaBase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RajuEEE/RewardModel_RobertaBase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RajuEEE/RewardModel_RobertaBase")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RajuEEE/RewardModel_RobertaBase") model = AutoModelForSequenceClassification.from_pretrained("RajuEEE/RewardModel_RobertaBase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RajuEEE/RewardModel_RobertaBase: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/RajuEEE/RewardModel_RobertaBase/resolve/main/training_args.bin
- Command line
-
hf download hf://RajuEEE/RewardModel_RobertaBase/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RajuEEE/RewardModel_RobertaBase/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- d5ecaaf2bf36883df47c7c1770a9c1f1065ff094ee704194d2613fe641658ec4
- Size of remote file:
- 5.11 kB
- SHA256:
- 9c32164d7d1fbb4be5ff1def9ff4334ea1b25181842232dbc60d27fe502bc651
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