Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use hydrochii/text_classify_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hydrochii/text_classify_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hydrochii/text_classify_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hydrochii/text_classify_model") model = AutoModelForSequenceClassification.from_pretrained("hydrochii/text_classify_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hydrochii/text_classify_model: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/hydrochii/text_classify_model/resolve/main/training_args.bin
- Command line
-
hf download hf://hydrochii/text_classify_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hydrochii/text_classify_model/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 4d8328c7ecb1b128017f34f4b9a5583fc1bf4ab89be7a406aa7e64be274991ab
- Size of remote file:
- 4.16 kB
- SHA256:
- a31a8ccf0f6b508bb64d1d26d86a45e933a12b10407bfef358063326032a26a4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.