Instructions to use StaAhmed/Model_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StaAhmed/Model_QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="StaAhmed/Model_QA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("StaAhmed/Model_QA") model = AutoModelForQuestionAnswering.from_pretrained("StaAhmed/Model_QA") - Notebooks
- Google Colab
- Kaggle
Training in progress epoch 0
Browse files- README.md +5 -6
- added_tokens.json +1 -1
- config.json +2 -2
- spm.model +2 -2
- tf_model.h5 +2 -2
- tokenizer.json +2 -2
- tokenizer_config.json +1 -1
README.md
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license: mit
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base_model: microsoft/
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tags:
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- generated_from_keras_callback
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model-index:
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# StaAhmed/Model_QA
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This model is a fine-tuned version of [microsoft/
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It achieves the following results on the evaluation set:
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- Train Loss: 3.
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- Epoch:
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## Model description
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| Train Loss | Epoch |
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### Framework versions
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---
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license: mit
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base_model: microsoft/mdeberta-v3-base
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tags:
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- generated_from_keras_callback
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model-index:
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# StaAhmed/Model_QA
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 3.1406
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- Epoch: 0
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## Model description
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| Train Loss | Epoch |
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| 3.1406 | 0 |
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### Framework versions
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added_tokens.json
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"[MASK]":
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"[MASK]": 250101
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config.json
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{
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"_name_or_path": "microsoft/
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"architectures": [
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"DebertaV2ForQuestionAnswering"
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],
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"share_att_key": true,
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"transformers_version": "4.35.2",
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"type_vocab_size": 0,
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"vocab_size":
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}
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"_name_or_path": "microsoft/mdeberta-v3-base",
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"architectures": [
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"DebertaV2ForQuestionAnswering"
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],
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"share_att_key": true,
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"transformers_version": "4.35.2",
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"type_vocab_size": 0,
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"vocab_size": 251000
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}
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spm.model
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version https://git-lfs.github.com/spec/v1
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tf_model.h5
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tokenizer.json
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size 16331659
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tokenizer_config.json
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"single_word": false,
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"special": true
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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"250101": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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