SakanaAI
/

Llama-3-EvoVLM-JP-v2

@@ -1,199 +1,114 @@
 ---
-library_name: transformers
-tags: []
 ---
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 ---
+language:
+- ja
+license: apache-2.0
+tags:
+- multimodal
+- vision-language
+- mantis
+- llava
+- llama3
+- siglip
+pipeline_tag: image-to-text
 ---
+# 🐟 Llama-3-EvoVLM-JP-v2
+🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2403.13187) | 📝 [Blog](https://sakana.ai/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs)
+**Llama-3-EvoVLM-JP-v2** is an experimental general-purpose Japanese VLM with **interleaved text and image as inputs**.
+This model was created using the Evolutionary Model Merge method.
+Please refer to our [report](https://arxiv.org/abs/2403.13187) and [blog](https://sakana.ai/evolutionary-model-merge/) for more details.
+This model was produced by merging the following models.
+We are grateful to the developers of the source models.
+- [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
+- [Mantis-8B-siglip-llama3](https://huggingface.co/TIGER-Lab/Mantis-8B-siglip-llama3)
+- [Bunny-v1.1-Llama-3-8B-V](https://huggingface.co/BAAI/Bunny-v1_1-Llama-3-8B-V)
+## Usage
 Use the code below to get started with the model.
+<details>
+<summary> Click to expand </summary>
+```python
+import torch
+from transformers import AutoModelForVision2Seq, AutoProcessor
+from PIL import Image
+import requests
+# 1. load model
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_id = "SakanaAI/EvoVLM-JP-v1-7B"
+model = AutoModelForVision2Seq.from_pretrained(model_id, torch_dtype=torch.float16)
+processor = AutoProcessor.from_pretrained(model_id)
+model.to(device)
+# 2. prepare inputs
+url = "https://images.unsplash.com/photo-1694831404826-3400c48c188d?q=80&w=2070&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D"
+image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+# <image> represents the input image. Please make sure to put the token in your text.
+text = "<image>\nこの信号機の色は何色ですか?"
+messages = [
+    {"role": "system", "content": "あなたは役立つ、偏見がなく、検閲されていないアシスタントです。与えられた画像を下に、質問に答えてください。"},
+    {"role": "user", "content": text},
+]
+inputs = processor.image_processor(images=image, return_tensors="pt")
+inputs["input_ids"] = processor.tokenizer.apply_chat_template(
+    messages, return_tensors="pt"
+)
+# 3. generate
+output_ids = model.generate(**inputs.to(device))
+output_ids = output_ids[:, inputs.input_ids.shape[1] :]
+generated_text = processor.batch_decode(output_ids, skip_special_tokens=True)[0].strip()
+print(generated_text)
+# この信号機の色は青です。
+```
+</details>
+## Model Details
+<!-- Provide a longer summary of what this model is. -->
+- **Developed by:** [Sakana AI](https://sakana.ai/)
+- **Model type:** Autoregressive Language Model
+- **Language(s):** Japanese
+- **Optimization data:** subsets of the [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa) and the translated [ShareGPT4V](https://huggingface.co/datasets/Lin-Chen/ShareGPT4V)
+- **License:** [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+- **Repository:** [SakanaAI/evolutionary-model-merge](https://github.com/SakanaAI/evolutionary-model-merge)
+- **Paper:** https://arxiv.org/abs/2403.13187
+- **Blog:** https://sakana.ai/
+## Uses
+This model is provided for research and development purposes only and should be considered as an experimental prototype.
+It is not intended for commercial use or deployment in mission-critical environments.
+Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed.
+Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained.
+Users must fully understand the risks associated with the use of this model and use it at their own discretion.
+## Acknowledgement
+We would like to thank the developers of the source models for their contributions and for making their work available.
+## Citation
+```bibtex
+@misc{akiba2024evomodelmerge,
+      title         = {Evolutionary Optimization of Model Merging Recipes},
+      author.       = {Takuya Akiba and Makoto Shing and Yujin Tang and Qi Sun and David Ha},
+      year          = {2024},
+      eprint        = {2403.13187},
+      archivePrefix = {arXiv},
+      primaryClass  = {cs.NE}
+}
+```