Text Classification
Transformers
PyTorch
ONNX
Safetensors
English
bert
Trained with AutoTrain
lam
text-embeddings-inference
Instructions to use biglam/autotrain-beyond-the-books with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biglam/autotrain-beyond-the-books with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="biglam/autotrain-beyond-the-books")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("biglam/autotrain-beyond-the-books") model = AutoModelForSequenceClassification.from_pretrained("biglam/autotrain-beyond-the-books") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03851b4696bd3128193867896f2102fadc6aec1e19fb860825771d5a9a12fd4f
- Size of remote file:
- 438 MB
- SHA256:
- 4eaf7cf5d964aea762edaaae81a7d7cf7d43ae061528765a2a3fa794da792f65
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