Instructions to use ManopeDavid/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManopeDavid/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ManopeDavid/my_awesome_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ManopeDavid/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("ManopeDavid/my_awesome_qa_model") - Notebooks
- Google Colab
- Kaggle
Commit 路
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Parent(s): 465e82d
Training in progress epoch 1
Browse files- README.md +4 -3
- tf_model.h5 +1 -1
README.md
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss:
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- Validation Loss:
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- Epoch:
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## Model description
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 3.4977 | 2.2290 | 0 |
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### Framework versions
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 1.9157
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- Validation Loss: 1.8993
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- Epoch: 1
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## Model description
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 3.4977 | 2.2290 | 0 |
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| 1.9157 | 1.8993 | 1 |
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### Framework versions
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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size 265583592
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version https://git-lfs.github.com/spec/v1
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size 265583592
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