Text Classification
Transformers
TensorFlow
Safetensors
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Wasifjafri/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wasifjafri/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Wasifjafri/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Wasifjafri/test") model = AutoModelForSequenceClassification.from_pretrained("Wasifjafri/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Wasifjafri/test: direct link, hf CLI and curl.
- Browser
- Download file 985 Bytes
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https://huggingface.co/Wasifjafri/test/resolve/main/README.md
- Command line
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hf download hf://Wasifjafri/test/README.md
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curl -L -o README.md https://huggingface.co/Wasifjafri/test/resolve/main/README.md
985 Bytes
| library_name: transformers | |
| license: apache-2.0 | |
| base_model: distilbert-base-uncased | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: test | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should | |
| probably proofread and complete it, then remove this comment. --> | |
| # test | |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - optimizer: None | |
| - training_precision: float32 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.48.3 | |
| - TensorFlow 2.18.0 | |
| - Tokenizers 0.21.0 | |