Instructions to use Zenith754/goodreads-bert-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zenith754/goodreads-bert-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zenith754/goodreads-bert-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zenith754/goodreads-bert-classifier") model = AutoModelForSequenceClassification.from_pretrained("Zenith754/goodreads-bert-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-375/optimizer.pt from Zenith754/goodreads-bert-classifier: direct link, hf CLI and curl.
- Browser
- Download file 526 MB
-
https://huggingface.co/Zenith754/goodreads-bert-classifier/resolve/main/checkpoint-375/optimizer.pt
- Command line
-
hf download hf://Zenith754/goodreads-bert-classifier/checkpoint-375/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Zenith754/goodreads-bert-classifier/resolve/main/checkpoint-375/optimizer.pt
526 MB
- Xet hash:
- cf5b3260b98218efefbd7a49e45bf8615fa66ccfe8229eeb9cccde3c1b732471
- Size of remote file:
- 526 MB
- SHA256:
- 2e2f2eec3fc67bd0ff4a86dfa22aa9e69279a48227945ea7fde9ecf45c0dde41
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