Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Kamsi08/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kamsi08/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kamsi08/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kamsi08/results") model = AutoModelForSequenceClassification.from_pretrained("Kamsi08/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bf48fee5dcc8aa4b68b849096700ce7925081fb2353621aa1346fcbe8b2c4c6
- Size of remote file:
- 5.78 kB
- SHA256:
- 67c3728f1b0fce1d622975376806fe0e11411f7ebd23e524b02896b0e5c5e860
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