Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Theoreticallyhugo/distilbert_B001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/distilbert_B001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Theoreticallyhugo/distilbert_B001")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/distilbert_B001") model = AutoModelForSequenceClassification.from_pretrained("Theoreticallyhugo/distilbert_B001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Theoreticallyhugo/distilbert_B001: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/Theoreticallyhugo/distilbert_B001/resolve/main/training_args.bin
- Command line
-
hf download hf://Theoreticallyhugo/distilbert_B001/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Theoreticallyhugo/distilbert_B001/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 78907c248c103218f3309dd8f666037cc8338fe5f128560e00868367f33eaeef
- Size of remote file:
- 4.66 kB
- SHA256:
- 96fec106080c0fe278f2ca511650e0ce666e2f6412051fd2b9a54381a327ce49
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