Instructions to use csatapathy/interview-ratings-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csatapathy/interview-ratings-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="csatapathy/interview-ratings-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("csatapathy/interview-ratings-bert") model = AutoModelForSequenceClassification.from_pretrained("csatapathy/interview-ratings-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from csatapathy/interview-ratings-bert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/csatapathy/interview-ratings-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://csatapathy/interview-ratings-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/csatapathy/interview-ratings-bert/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3df76246495b42b6aa004b9ae3f8826c7ed7b3bf2580e8ffd8129419b1449281
- Size of remote file:
- 438 MB
- SHA256:
- 530c42a55b6fb5ea4e9282146248cad2ea1bd2faae78b7b1dc4d3862490e4fb8
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