Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ehottl/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehottl/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ehottl/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ehottl/results") model = AutoModelForSequenceClassification.from_pretrained("ehottl/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df9a5369279f103406fcc9498dc9f5e2a00310566c4e027214f8bb9048e01717
- Size of remote file:
- 5.3 kB
- SHA256:
- aea02112cf098e1413fb94e5f4d499077cae5184bf789aaab240a0f4355ea33b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.