Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use bakch92/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bakch92/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bakch92/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bakch92/results") model = AutoModelForSequenceClassification.from_pretrained("bakch92/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc1e08c2ba60324ea5a5767d37bc27b5d47bcf66b202368e539990fcb59570c7
- Size of remote file:
- 5.18 kB
- SHA256:
- c53cf703dfd58a574c28fb73197ed28205a83e0d78166b99800b04adeae276ed
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