Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use conflick0/impact-cat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use conflick0/impact-cat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="conflick0/impact-cat")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("conflick0/impact-cat") model = AutoModelForSequenceClassification.from_pretrained("conflick0/impact-cat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d88bf8a28dee948e88301631144478bb2fd9af9c1298ebf55fc87d4e93b06bb
- Size of remote file:
- 4.92 kB
- SHA256:
- 804f96cf9be880603d0fd3056bdc272ad7838cb53033b4a2be90b45a80b96a75
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.