Instructions to use YanJiangJerry/sentiment-roberta-e6-b16-data2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YanJiangJerry/sentiment-roberta-e6-b16-data2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YanJiangJerry/sentiment-roberta-e6-b16-data2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YanJiangJerry/sentiment-roberta-e6-b16-data2") model = AutoModelForSequenceClassification.from_pretrained("YanJiangJerry/sentiment-roberta-e6-b16-data2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YanJiangJerry/sentiment-roberta-e6-b16-data2: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/YanJiangJerry/sentiment-roberta-e6-b16-data2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YanJiangJerry/sentiment-roberta-e6-b16-data2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YanJiangJerry/sentiment-roberta-e6-b16-data2/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 43d6769b7e7341ddd2d483b91b0aa33a6e13eea54df886c1ed0362a874b1f6e4
- Size of remote file:
- 1.42 GB
- SHA256:
- 3ad34e065815b1bc7feea6f130bf9d37de204c6402f8bdd6b3bb30162263d0ee
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