Text Classification
Transformers
PyTorch
bert
Generated from Trainer
sibyl
Eval Results (legacy)
text-embeddings-inference
Instructions to use fabriceyhc/bert-base-uncased-amazon_polarity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabriceyhc/bert-base-uncased-amazon_polarity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fabriceyhc/bert-base-uncased-amazon_polarity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fabriceyhc/bert-base-uncased-amazon_polarity") model = AutoModelForSequenceClassification.from_pretrained("fabriceyhc/bert-base-uncased-amazon_polarity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fabriceyhc/bert-base-uncased-amazon_polarity: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fabriceyhc/bert-base-uncased-amazon_polarity/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fabriceyhc/bert-base-uncased-amazon_polarity/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 7f867d4083128b37b6795abd2994a27b342f29febd89ef28b7839567d4ae3682
- Size of remote file:
- 438 MB
- SHA256:
- 037b49d4da34f299f74533c074a9d31f444454ed561d8f58b689eedef37c7264
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