Text Classification
Transformers
TensorBoard
Safetensors
opt
trl
reward-trainer
Generated from Trainer
Instructions to use SiMajid/value_reward_modeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiMajid/value_reward_modeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SiMajid/value_reward_modeling")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SiMajid/value_reward_modeling") model = AutoModelForSequenceClassification.from_pretrained("SiMajid/value_reward_modeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SiMajid/value_reward_modeling: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/SiMajid/value_reward_modeling/resolve/main/training_args.bin
- Command line
-
hf download hf://SiMajid/value_reward_modeling/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SiMajid/value_reward_modeling/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- c480bb528bc0e435913ec05e5f88b66ffac797f2f9595fdb21256f1beec4818f
- Size of remote file:
- 5.18 kB
- SHA256:
- 67223f74bae90f4f86b467b74b6a3594a16d7067d7912751dcfa1d3b9b30e167
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