Improve model card: Add pipeline tag and library name
Browse filesThis PR improves the model card by adding the `image-feature-extraction` pipeline tag and specifying `terratorch` as the library name. This enhances discoverability and provides more context for users. The PR also links to the paper on which the model is based at the top of the model card. It should now be easier for users to locate and evaluate the model's performance. It also links to the base model's paper, ensuring people can find it at https://huggingface.co/papers/2310.18660.
README.md
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---
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license: apache-2.0
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---
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# Model Card for granite-geospatial-biomass
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<p align="center" width="100%">
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<img src="https://github.com/ibm-granite/granite-geospatial-biomass/blob/main/biomass-image.jpeg?raw=true" width="600">
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</p>
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```python
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from terratorch.cli_tools import LightningInferenceModel
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ckpt_path = hf_hub_download(repo_id="ibm-granite/granite-geospatial-biomass", filename="biomass_model.ckpt")
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config_path = hf_hub_download(repo_id="ibm-granite/granite-geospatial-biomass", filename="config.yaml")
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---
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license: apache-2.0
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library_name: terratorch
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pipeline_tag: image-feature-extraction
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---
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# Model Card for granite-geospatial-biomass
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This model is based on the paper [TerraTorch: The Geospatial Foundation Models Toolkit](https://huggingface.co/papers/2503.20563).
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<p align="center" width="100%">
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<img src="https://github.com/ibm-granite/granite-geospatial-biomass/blob/main/biomass-image.jpeg?raw=true" width="600">
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</p>
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```python
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from terratorch.cli_tools import LightningInferenceModel
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from huggingface_hub import hf_hub_download
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ckpt_path = hf_hub_download(repo_id="ibm-granite/granite-geospatial-biomass", filename="biomass_model.ckpt")
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config_path = hf_hub_download(repo_id="ibm-granite/granite-geospatial-biomass", filename="config.yaml")
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