Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/Upload_test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/Upload_test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/Upload_test_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/Upload_test_model") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/Upload_test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cfdaf5dea0e83c2944a8e98b6e0b47061a9a9be1b7c4d4a67097665ff320d44
- Size of remote file:
- 3.58 kB
- SHA256:
- 88b32cb0933868b540e388618c50b93abda29871e42f44de8407813ea6341dec
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