Instructions to use shahrukhx01/bert-mini-sentiment-reward-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahrukhx01/bert-mini-sentiment-reward-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shahrukhx01/bert-mini-sentiment-reward-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shahrukhx01/bert-mini-sentiment-reward-model") model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/bert-mini-sentiment-reward-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shahrukhx01/bert-mini-sentiment-reward-model: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/shahrukhx01/bert-mini-sentiment-reward-model/resolve/main/training_args.bin
- Command line
-
hf download hf://shahrukhx01/bert-mini-sentiment-reward-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shahrukhx01/bert-mini-sentiment-reward-model/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- fb666e94f5b409b792e64daa739cb4799a91e73005f82ca6bbbf3d33988c5007
- Size of remote file:
- 3.64 kB
- SHA256:
- 8dd74454c940fac7049519b3aaea69f5887d4e8169d3e4a68232127e265bf5a3
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