Text Classification
Transformers
Safetensors
distilbert
sentiment-analysis
customer-support
Generated from Trainer
Eval Results (legacy)
Instructions to use bharatttt/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bharatttt/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bharatttt/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bharatttt/results") model = AutoModelForSequenceClassification.from_pretrained("bharatttt/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea9a48cc92ea873d89a859489b857628ccdaf82ed62de46b34dafb20be42267d
- Size of remote file:
- 5.14 kB
- SHA256:
- 22d86007df769f8e3e7f67d539c639bb79b31a8b03a11f3744a9ba2530cc1616
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