Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Theoreticallyhugo/B001_cleaned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/B001_cleaned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Theoreticallyhugo/B001_cleaned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/B001_cleaned") model = AutoModelForSequenceClassification.from_pretrained("Theoreticallyhugo/B001_cleaned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72b5cca62ee624b9344efc100ffc182ee1b4538e185d343ebc1735a63fecf7dc
- Size of remote file:
- 4.66 kB
- SHA256:
- 407414b3b4afc4e0ff2675dd8fbb2bd08941d4c4f102286ad4ed689a634d419d
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