Instructions to use ChunLok/CAM_sentiment_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChunLok/CAM_sentiment_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ChunLok/CAM_sentiment_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ChunLok/CAM_sentiment_model") model = AutoModelForSequenceClassification.from_pretrained("ChunLok/CAM_sentiment_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ChunLok/CAM_sentiment_model: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/ChunLok/CAM_sentiment_model/resolve/main/training_args.bin
- Command line
-
hf download hf://ChunLok/CAM_sentiment_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ChunLok/CAM_sentiment_model/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 7cfc6aca24b5131766947fa7eee82a4c5276423fc1e4f8403c130ad054f94a71
- Size of remote file:
- 4.66 kB
- SHA256:
- e493d05d535a8b527c50ced6e23650d053affe4f2916fdac526d373e37de58a9
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