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README.md

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-license: apache-2.0
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+---
+inference: false
+pipeline_tag: image-text-to-text
+language:
+- en
+---
+
+<br>
+<br>
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/F2d0zMtwUqPKtOrbMu0Gr.jpeg" alt="image/jpeg" style="width:10%;">
+
+# SliME Model Card
+
+## Model details
+
+**Model type:**
+SliME is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data.
+It is an auto-regressive language model, based on the transformer architecture.
+Base LLM: [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/_dsyhwdanIgUPtejamXmX.png)
+
+**Paper or resources for more information:**
+https://github.com/yfzhang114/SliME
+
+## License
+Llama 3 is licensed under the LLAMA 3 Community License, 
+Copyright (c) Meta Platforms, Inc. All Rights Reserved.
+
+**Where to send questions or comments about the model:**
+https://github.com/yfzhang114/SliME/issues
+
+## Intended use
+**Primary intended uses:**
+The primary use of SliME is research on large multimodal models and chatbots.
+
+**Primary intended users:**
+The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
+
+## Training dataset
+- SharedGPT4v sft data
+- SMR data
+
+## Evaluation dataset
+A collection of 15 benchmarks, including 5 academic VQA benchmarks and 10 recent benchmarks specifically proposed for instruction-following LMMs.
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/dLXygEd23t-xImhSBLlta.png)