Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Vyke2000/Nephased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vyke2000/Nephased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vyke2000/Nephased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vyke2000/Nephased") model = AutoModelForSequenceClassification.from_pretrained("Vyke2000/Nephased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Vyke2000/Nephased: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Vyke2000/Nephased/resolve/main/training_args.bin
- Command line
-
hf download hf://Vyke2000/Nephased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Vyke2000/Nephased/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- a75922ec4e01809ae1e6407827a41d7331c423c8d3c2de745a849f5584dcdfa5
- Size of remote file:
- 5.37 kB
- SHA256:
- acf6f60c2949e5d9a00f9189c6f0b3145db8edb1eb1d6e1e21290b5afdb59c3b
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