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README.md
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@@ -22,6 +22,14 @@ This is a copy of the original [Molmo 7B-D model card](https://huggingface.co/al
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**Note: The following implementation is a community-contributed endpoint handler and is not an official implementation. For the official model and its usage, please refer to the [official Molmo 7B-D model page](https://huggingface.co/allenai/Molmo-7B-D-0924).**
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If you've deployed the model using Hugging Face's Inference Endpoints with a community-contributed handler, you can use it with the following code:
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```python
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**Note: The following implementation is a community-contributed endpoint handler and is not an official implementation. For the official model and its usage, please refer to the [official Molmo 7B-D model page](https://huggingface.co/allenai/Molmo-7B-D-0924).**
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You should see a `Deploy` via Inference Endpoints option at the top of this model card.
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/60107b385ac3e86b3ea4fc34/kHR0wO_GchczmsmHtjJ1u.png)
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Currently, this handler uses `bloat16` for inference. The original authors found some differences in results vs using `float32` weights.
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I didn't find results that degraded much in my initial experiments, but I may change this implementation in the future.
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If you've deployed the model using Hugging Face's Inference Endpoints with a community-contributed handler, you can use it with the following code:
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```python
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