Instructions to use YanJiangJerry/sentiment-roberta_base-e4-b16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YanJiangJerry/sentiment-roberta_base-e4-b16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YanJiangJerry/sentiment-roberta_base-e4-b16")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YanJiangJerry/sentiment-roberta_base-e4-b16") model = AutoModelForSequenceClassification.from_pretrained("YanJiangJerry/sentiment-roberta_base-e4-b16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YanJiangJerry/sentiment-roberta_base-e4-b16: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/YanJiangJerry/sentiment-roberta_base-e4-b16/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YanJiangJerry/sentiment-roberta_base-e4-b16/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YanJiangJerry/sentiment-roberta_base-e4-b16/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 6df6b0be11622513f68d7547cde620997c7a34bd0186da44ae2bb6eec39015bb
- Size of remote file:
- 499 MB
- SHA256:
- 22937f52cba0a36a464a0730c89982cfa23471c31a84105c41eaff608a75b9d7
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