Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use devinitorg/cdp-multi-classifier-weighted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devinitorg/cdp-multi-classifier-weighted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devinitorg/cdp-multi-classifier-weighted")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devinitorg/cdp-multi-classifier-weighted") model = AutoModelForSequenceClassification.from_pretrained("devinitorg/cdp-multi-classifier-weighted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from devinitorg/cdp-multi-classifier-weighted: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/devinitorg/cdp-multi-classifier-weighted/resolve/main/training_args.bin
- Command line
-
hf download hf://devinitorg/cdp-multi-classifier-weighted/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/devinitorg/cdp-multi-classifier-weighted/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 53a2cce2eb0ffde2eb4457abeccd0d9c27f606bc6c2d3aebf4d3d8dfc70682bf
- Size of remote file:
- 4.54 kB
- SHA256:
- a35dad46a29f210007d8e29f6c83a2c3eb0f30ace14d38272435b3268487743b
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