Instructions to use velvrix/roberta_Uniacco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use velvrix/roberta_Uniacco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="velvrix/roberta_Uniacco")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("velvrix/roberta_Uniacco") model = AutoModelForSequenceClassification.from_pretrained("velvrix/roberta_Uniacco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from velvrix/roberta_Uniacco: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/velvrix/roberta_Uniacco/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://velvrix/roberta_Uniacco/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/velvrix/roberta_Uniacco/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- d4f44424f5b034096784629af64880bfcd81635c0fb2abfd2c36659546346fec
- Size of remote file:
- 499 MB
- SHA256:
- 087ab90a715d89133e5dd02309d9b774110adc5070e07c81ce1a6ed23e44022c
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