Text Classification
Transformers
PyTorch
TensorBoard
English
French
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer") model = AutoModelForSequenceClassification.from_pretrained("Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer: direct link, hf CLI and curl.
- Browser
- Download file 975 Bytes
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https://huggingface.co/Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer/resolve/main/README.md
- Command line
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hf download hf://Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer/README.md
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curl -L -o README.md https://huggingface.co/Ahmedgr/DistilBert_Fine_tune_QuestionVsAnswer/resolve/main/README.md
975 Bytes
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: DistilBert_Fine_tune_QuestionVsAnswer | |
| results: [] | |
| license: mit | |
| language: | |
| - en | |
| - fr | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # DistilBert_Fine_tune_QuestionVsAnswer | |
| This model was trained from scratch on an unknown dataset. | |
| ## 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: | |
| - learning_rate: 5e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 0 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Framework versions | |
| - Transformers 4.17.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Tokenizers 0.11.6 |