Instructions to use velvrix/truefoundary_sentimental_RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use velvrix/truefoundary_sentimental_RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="velvrix/truefoundary_sentimental_RoBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("velvrix/truefoundary_sentimental_RoBERTa") model = AutoModelForSequenceClassification.from_pretrained("velvrix/truefoundary_sentimental_RoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from velvrix/truefoundary_sentimental_RoBERTa: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/velvrix/truefoundary_sentimental_RoBERTa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://velvrix/truefoundary_sentimental_RoBERTa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/velvrix/truefoundary_sentimental_RoBERTa/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- e45073309bff054f7070d31a4e544a2e159ee2e4f50128d0fb239b37da5c620a
- Size of remote file:
- 499 MB
- SHA256:
- e2c9ffcfd82378eb1882d699c0dc7da22c864b38c0d3905f85d001e6dff02a2f
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