shinyice
/

chatvector-llava-v1.5-plus-houou-v3-7b

@@ -1,199 +1,120 @@
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 library_name: transformers
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 ---
+license: cc-by-nc-4.0
+language:
+- ja
 library_name: transformers
+tags:
+- vision
+- image-captioning
 ---
+# Chatvector-llava-v1.6-vicuna-plus-Houou-v3-7b Model Card
+# Model Details
+※好奇心から生まれたモデルです。精度は保証できません。<br>
+chatvector-llava-v1.6-vicuna-plus-houou-v3-7bは日本語で画像を説明することが可能なVLMです。<br>
+[Chat Vector](https://arxiv.org/abs/2310.04799)の手法に影響を受けています。
+このモデルはChat Vectorを参考に[llava-v1.5-7b](https://huggingface.co/liuhaotian/llava-v1.5-7b)と[houou-instruction-7b-v3](https://huggingface.co/moneyforward/houou-instruction-7b-v3)、[Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf)
+の重みを以下のように加減算することで作成してみました。<br>
+```
+houou-instruction-7b-v3 + (llava-v1.5-7b - Llama-2-7b-hf)
+```
+次のプログラムは引用させていただいたサイトにあったものをベースにしています。以下文献もぜひご覧ください。
 ## Uses
+```sh
+git clone https://github.com/haotian-liu/LLaVA.git
+cd LLaVA
+pip install -e .
+```
+```python
+import requests
+import torch
+import transformers
+from PIL import Image
+from transformers.generation.streamers import TextStreamer
+from llava.constants import DEFAULT_IMAGE_TOKEN, IMAGE_TOKEN_INDEX
+from llava.conversation import conv_templates, SeparatorStyle
+from llava.model.language_model.llava_llama import LlavaLlamaForCausalLM
+from llava.mm_utils import tokenizer_image_token, process_images
+model_path = "shinyice/chatvector-llava-v1.5-plus-houou-v3-7b"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+image_url = "https://huggingface.co/rinna/bilingual-gpt-neox-4b-minigpt4/resolve/main/sample.jpg"
+temperature = 0.0
+top_p = 1.0
+max_new_tokens = 256
+model = LlavaLlamaForCausalLM.from_pretrained(
+    model_path,
+    device_map=device,
+    low_cpu_mem_usage=True,
+    use_safetensors=True,
+    torch_dtype=torch.float16,
+).eval()
+tokenizer = transformers.AutoTokenizer.from_pretrained(
+    model_path,
+    model_max_length=1024,
+    padding_side="right",
+    use_fast=False,
+)
+model.get_model().vision_tower.load_model()
+model = model.to(device)
+eos_token_id_list = [
+    tokenizer.eos_token_id,
+    tokenizer.bos_token_id,
+]
+image = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
+if not isinstance(image, list):
+    image = [image]
+image_tensor = process_images(image, model.get_model().vision_tower.image_processor, model.config)
+image_sizes = [img.size for img in image]
+if isinstance(image_tensor, list):
+    image_tensor = [img.to(model.device, dtype=torch.float16) for img in image_tensor]
+else:
+    image_tensor = image_tensor.to(device, dtype=torch.float16)
+image_sizes_tensor = torch.tensor(image_sizes, dtype=torch.int32, device=device)
+conv_mode = "v1"
+conv = conv_templates[conv_mode].copy()
+prompt = "猫の隣には何がありますか？"
+inp = DEFAULT_IMAGE_TOKEN + '\n' + prompt
+conv.append_message(conv.roles[0], inp)
+conv.append_message(conv.roles[1], None)
+prompt = conv.get_prompt()
+input_ids = tokenizer_image_token(
+    prompt,
+    tokenizer,
+    IMAGE_TOKEN_INDEX,
+    return_tensors='pt'
+).unsqueeze(0)
+with torch.inference_mode():
+    output = model.generate(
+        inputs=input_ids,
+        images=image_tensor,
+        image_sizes=image_sizes_tensor,
+        do_sample=True if temperature > 0 else False,
+        temperature=temperature,
+        top_p=top_p,
+        max_new_tokens=max_new_tokens,
+        use_cache=True,
+        eos_token_id=eos_token_id_list,
+    )
+print(tokenizer.decode(output[0]))
+```
+## Bibliography
+- [Chat VectorでLLaVAを日本語対応させる](https://zenn.dev/toshi_456/articles/0166a6eaa81c7b)
+- [Chat Vectorを使って日本語LLMをチャットモデルに改造する](https://qiita.com/jovyan/items/ee6affa5ee5bdaada6b4)