Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use hf-tuner/bert-banking-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tuner/bert-banking-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tuner/bert-banking-intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tuner/bert-banking-intent") model = AutoModelForSequenceClassification.from_pretrained("hf-tuner/bert-banking-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hf-tuner/bert-banking-intent: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/hf-tuner/bert-banking-intent/resolve/main/training_args.bin
- Command line
-
hf download hf://hf-tuner/bert-banking-intent/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hf-tuner/bert-banking-intent/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 509970234eeb7c919bcd0aeea5ccecba635455c220f08ee1a94a8f52d0155631
- Size of remote file:
- 5.84 kB
- SHA256:
- 531ee9a31b65279c76cd00ad90aaad19a7b9a1732905d48edda58972d9555735
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