Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use RajuEEE/RewardModel_RobertaBase_GPT_Data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RajuEEE/RewardModel_RobertaBase_GPT_Data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RajuEEE/RewardModel_RobertaBase_GPT_Data")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RajuEEE/RewardModel_RobertaBase_GPT_Data") model = AutoModelForSequenceClassification.from_pretrained("RajuEEE/RewardModel_RobertaBase_GPT_Data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RajuEEE/RewardModel_RobertaBase_GPT_Data: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/RajuEEE/RewardModel_RobertaBase_GPT_Data/resolve/main/training_args.bin
- Command line
-
hf download hf://RajuEEE/RewardModel_RobertaBase_GPT_Data/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RajuEEE/RewardModel_RobertaBase_GPT_Data/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 19d9809faeca56c33e47c64f3cee1b791ca6052169d504a3ac5693939553ce9c
- Size of remote file:
- 5.11 kB
- SHA256:
- 9dc61c3f16a2e61559eb86a0c9cef692d9319359e15328aaf016d6ce3587a35c
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