Instructions to use breadlicker45/test-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breadlicker45/test-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="breadlicker45/test-class")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("breadlicker45/test-class") model = AutoModelForSequenceClassification.from_pretrained("breadlicker45/test-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload 7 files
77c9b7a
-
Upload 7 files
261fd16 -
Delete model.safetensors
1b161c6 -
Upload 8 files
f82e8f8 -
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (43e26ed327cb932606660f2515fa401bd4687118) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>29f6ea3 -
Rename tokenizer (2).json to tokenizer.json
2f16948 -
Upload tokenizer (2).json
88bd16f -
Upload 8 files
1dfdfab -
initial commit
matthew null18964c0