Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use thanhcong2001/Multiple_Labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thanhcong2001/Multiple_Labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thanhcong2001/Multiple_Labels")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thanhcong2001/Multiple_Labels") model = AutoModelForSequenceClassification.from_pretrained("thanhcong2001/Multiple_Labels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thanhcong2001/Multiple_Labels: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/thanhcong2001/Multiple_Labels/resolve/main/training_args.bin
- Command line
-
hf download hf://thanhcong2001/Multiple_Labels/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thanhcong2001/Multiple_Labels/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 8e7c0db46ab78ef17866d5c82f79405ac6c474a741e9b3f68617de55c55ba1c4
- Size of remote file:
- 5.78 kB
- SHA256:
- 984f64e8b195d810cb8865fffe67a359ab67c623f76e57d9a59eb02a4067ffdf
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