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README.md

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+---
+language:
+- ja
+license: apache-2.0
+tags:
+- llava
+- vision-language
+pipeline_tag: image-to-text
+---
+
+
+# 🐟 EvoVLM-JP-v1-7B
+
+🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2403.13187) | 📝 [Blog](https://sakana.ai/evolutionary-model-merge/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs)
+
+
+**EvoVLM-JP-v1-7B** is an experimental general-purpose Japanese VLM. 
+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.
+
+- [Shisa Gamma 7B v1](https://huggingface.co/augmxnt/shisa-gamma-7b-v1)
+- [LLaVA-1.6-Mistral-7B](https://huggingface.co/liuhaotian/llava-v1.6-mistral-7b)
+
+
+
+## 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:** a subset of [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa)
+- **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/evolutionary-model-merge
+
+
+## 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}
+}
+```
+
+
+

added_tokens.json

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+  "<pad>": 32001
+}

config.json

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+  "architectures": [
+    "LlavaForConditionalGeneration"
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+  "model_type": "llava",
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+  "projector_hidden_act": "gelu",
+  "text_config": {
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+    "architectures": [
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+  "use_image_newline_parameter": true,
+  "vision_config": {
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+    "image_size": 336,
+    "intermediate_size": 4096,
+    "model_type": "clip_vision_model",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "patch_size": 14,
+    "projection_dim": 768,
+    "vocab_size": 32000
+  },
+  "vision_feature_layer": -2,
+  "vision_feature_select_strategy": "default",
+  "vocab_size": 32064
+}

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "max_new_tokens": 1024,
+  "num_beams": 5,
+  "pad_token_id": 32001,
+  "repetition_penalty": 1.5,
+  "transformers_version": "4.38.2"
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preprocessor_config.json

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+{
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+    "width": 336
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+  "size": {
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+}

special_tokens_map.json

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+{
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+    "single_word": false
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+    "single_word": false
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+}

tokenizer.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

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+  "pad_token": "<pad>",
+  "processor_class": "LlavaProcessor",
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+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}