Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`microsoft/resnet-152`](https://huggingface.co/microsoft/resnet-152) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.
How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.
**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.
For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).
This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).
If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!
@@ -6,12 +6,13 @@ datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: weeds_hfclass18
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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split: test
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args: default
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metrics:
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type: accuracy
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value: 0.7766666666666666
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- imagefolder
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metrics:
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- accuracy
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base_model: microsoft/resnet-152
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model-index:
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- name: weeds_hfclass18
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results:
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- task:
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type: image-classification
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name: Image Classification
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dataset:
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name: imagefolder
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type: imagefolder
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split: test
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args: default
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metrics:
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- type: accuracy
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value: 0.7766666666666666
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name: Accuracy
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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