Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sreenington/BERT-Ecommerce-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sreenington/BERT-Ecommerce-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sreenington/BERT-Ecommerce-Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sreenington/BERT-Ecommerce-Classification") model = AutoModelForSequenceClassification.from_pretrained("Sreenington/BERT-Ecommerce-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sreenington/BERT-Ecommerce-Classification: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/Sreenington/BERT-Ecommerce-Classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Sreenington/BERT-Ecommerce-Classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sreenington/BERT-Ecommerce-Classification/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 785ae96a01f92e79c51f016a7eea42c70ec2dd99828591943144e9ea85693cb2
- Size of remote file:
- 4.6 kB
- SHA256:
- a1020b1b7ca52af093c8630f25dbfd165c01f839f655e060a288be5f5bcc10b9
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