Instructions to use EducativeCS2023/roberta-similarity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EducativeCS2023/roberta-similarity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EducativeCS2023/roberta-similarity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EducativeCS2023/roberta-similarity") model = AutoModelForSequenceClassification.from_pretrained("EducativeCS2023/roberta-similarity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EducativeCS2023/roberta-similarity: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/EducativeCS2023/roberta-similarity/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EducativeCS2023/roberta-similarity/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EducativeCS2023/roberta-similarity/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 154129849f77e156756ffa068275f0464f65a24d9173ed885aa0cef2943ec798
- Size of remote file:
- 499 MB
- SHA256:
- 204f123420b605e78ff3457f94863f5f0b087ec4906de664e5b9196610ab8ca4
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