Instructions to use DSI/personal_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSI/personal_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/personal_sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DSI/personal_sentiment") model = AutoModelForSequenceClassification.from_pretrained("DSI/personal_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DSI/personal_sentiment: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/DSI/personal_sentiment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DSI/personal_sentiment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DSI/personal_sentiment/resolve/main/pytorch_model.bin
651 MB
- Xet hash:
- 6c4b7b00bd7eea9a876aae7391e6286d7217e9f38b107e4f3704f7fb77be5296
- Size of remote file:
- 651 MB
- SHA256:
- a2c5d612b72a2b3504e320b1a4aee323bd5a765f0330ecb83bfd6e22e3f30efb
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