Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Overthrow4232/route_classifier_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Overthrow4232/route_classifier_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Overthrow4232/route_classifier_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Overthrow4232/route_classifier_v1") model = AutoModelForSequenceClassification.from_pretrained("Overthrow4232/route_classifier_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Overthrow4232/route_classifier_v1: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Overthrow4232/route_classifier_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://Overthrow4232/route_classifier_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Overthrow4232/route_classifier_v1/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- ba1e36e902110340ec3d26450fc3c3c9cc4a10384cba7be9f8c3393d2b073d2d
- Size of remote file:
- 4.92 kB
- SHA256:
- db59ad0236aa49572e6ee98a9e0e79f5611ace19d0f47467a903927e76b694c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.