fix: push

.gitignore

@@ -0,0 +1 @@
+dependency

requirements.txt

@@ -1,10 +1,8 @@
-torch
-transformers
-accelerate
+llava @ git+https://github.com/MM-FIRE/FIRE
 aiohttp
-fastapi
 httpx
 numpy
 peft
 sentencepiece
-protobuf
+protobuf
+loguru

src/model/model_llava.py

@@ -0,0 +1,61 @@
+from llava.model.builder import load_pretrained_model
+from llava.mm_utils import get_model_name_from_path, process_images, tokenizer_image_token
+from llava.constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN
+from llava.conversation import conv_templates
+
+from PIL import Image
+import requests
+import copy
+import torch
+from llava.mm_utils import process_images, tokenizer_image_token, get_model_name_from_path
+import spaces
+#model_path = "/scratch/TecManDep/A_Models/llava-v1.6-vicuna-7b"
+#conv_template = "vicuna_v1" # Make sure you use correct chat template for different models
+
+def load_llava_model():
+    model_path =  "Lin-Chen/open-llava-next-llama3-8b"
+    conv_template = "llama_v3"
+    model_name = get_model_name_from_path(model_path)
+    device = "cuda"
+    device_map = "auto"
+    tokenizer, model, image_processor, max_length = load_pretrained_model(
+        model_path, None, model_name, device_map=device_map) # Add any other thing you want to pass in llava_model_args
+
+    model.eval()
+    model.tie_weights()
+    return tokenizer, model, image_processor, conv_template
+
+tokenizer_llava, model_llava, image_processor_llava, conv_template_llava = load_llava_model()
+
+@spaces.GPU
+def inference():
+    image = Image.open("assets/example.jpg").convert("RGB")
+    device = "cuda"
+    image_tensor = process_images([image], image_processor_llava, model_llava.config)
+    image_tensor = image_tensor.to(dtype=torch.float16, device=device)
+
+    prompt = """<image>What is in the figure?"""
+    conv = conv_templates[conv_template_llava].copy()
+    conv.append_message(conv.roles[0], prompt)
+    conv.append_message(conv.roles[1], None)
+    prompt_question = conv.get_prompt()
+
+    input_ids = tokenizer_image_token(prompt_question, tokenizer_llava, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).to(device)
+    image_sizes = [image.size]
+    print(input_ids.shape, image_tensor.shape)
+    with torch.inference_mode():
+        cont = model_llava.generate(
+            input_ids,
+            images=image_tensor,
+            image_sizes=image_sizes,
+            do_sample=False,
+            temperature=0,
+            max_new_tokens=256,
+            use_cache=True
+        )
+    text_outputs = tokenizer_llava.batch_decode(cont, skip_special_tokens=True)
+    print(text_outputs)
+    return text_outputs
+
+if __name__ == "__main__":
+    inference()

src/serve/gradio_block_arena_vision_named.py

@@ -242,14 +242,14 @@ def add_text(
 
 def build_side_by_side_vision_ui_named(models, random_questions=None):
     notice_markdown = """
-# ⚔️  Vision Arena ⚔️ : Benchmarking VLMs in the Wild (FIRE-LLAVA VS. LLAVA)
+# ⚔️  Vision Arena ⚔️ : Benchmarking VLMs (FIRE-LLAVA VS. LLAVA)
 | [Blog](https://lmsys.org/blog/2023-05-03-arena/) | [GitHub](https://github.com/lm-sys/FastChat) | [Paper](https://arxiv.org/abs/2306.05685) | [Dataset](https://github.com/lm-sys/FastChat/blob/main/docs/dataset_release.md) | [Twitter](https://twitter.com/lmsysorg) | [Discord](https://discord.gg/HSWAKCrnFx) |
 
 ## 📜 Rules
 - Chat with any two models side-by-side and vote!
 - You can continue chatting for multiple rounds.
 - Click "Clear history" to start a new round.
-- You can only chat with <span style='color: #DE3163; font-weight: bold'>one image per conversation</span>. You can upload images less than 15MB. Click the "Random Example" button to chat with a random image.
+- You can only chat with <span style='color: #DE3163; font-weight: bold'>one image per conversation</span>. You can upload images less than 15MB.
 
 **❗️ For research purposes, we log user prompts and images, and may release this data to the public in the future. Please do not upload any confidential or personal information.**