Create README.md

README.md

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+---
+language:
+- en
+tags:
+- llava
+- multimodal
+- qwen
+license: apache-2.0
+---
+# nanoLLaVA - Sub 1B Vision-Language Model
+
+<p align="center">
+  <img src="https://i.postimg.cc/d15k3YNG/nanollava.webp" alt="Logo" width="350">
+</p>
+
+## Description
+nanoLLaVA-1.5 is a "small but mighty" 1B vision-language model designed to run efficiently on edge devices. This is an update from the v1.0 version [qnguyen3/nanoLLaVA](https://huggingface.co/qnguyen3/nanoLLaVA)
+- **Base LLM**: [Quyen-SE-v0.1](https://huggingface.co/vilm/Quyen-SE-v0.1) (Qwen1.5-0.5B)
+- **Vision Encoder**: [google/siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384)
+
+| Model   | **VQA v2** | **TextVQA** | **ScienceQA** | **POPE** | **MMMU (Test)** | **MMMU (Eval)** | **GQA**  | **MM-VET** |
+|---------|--------|---------|-----------|------|-------------|-------------|------|--------|
+| nanoLLavA-1.0   | 70.84  | 46.71   | 58.97     | 84.1 | 28.6        | 30.4        | 54.79| 23.9   |
+| nanoLLavA-1.5   | TBD  | TBD   | TBD     | TBD | TBD        | TBD        | TBD| TBD   |
+
+## Training Data
+Training Data will be released later as I am still writing a paper on this. Expect the final final to be much more powerful than the current one.
+
+## Finetuning Code
+Coming Soon!!!
+
+## Usage
+You can use with `transformers` with the following script:
+
+```bash
+pip install -U transformers accelerate flash_attn
+```
+
+```python
+import torch
+import transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from PIL import Image
+import warnings
+
+# disable some warnings
+transformers.logging.set_verbosity_error()
+transformers.logging.disable_progress_bar()
+warnings.filterwarnings('ignore')
+
+# set device
+torch.set_default_device('cuda')  # or 'cpu'
+
+model_name = 'qnguyen3/nanoLLaVA-1.5'
+
+# create model
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map='auto',
+    trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(
+    model_name,
+    trust_remote_code=True)
+
+# text prompt
+prompt = 'Describe this image in detail'
+
+messages = [
+    {"role": "user", "content": f'<image>\n{prompt}'}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+print(text)
+
+text_chunks = [tokenizer(chunk).input_ids for chunk in text.split('<image>')]
+input_ids = torch.tensor(text_chunks[0] + [-200] + text_chunks[1], dtype=torch.long).unsqueeze(0)
+
+# image, sample images can be found in images folder
+image = Image.open('/path/to/image.png')
+image_tensor = model.process_images([image], model.config).to(dtype=model.dtype)
+
+# generate
+output_ids = model.generate(
+    input_ids,
+    images=image_tensor,
+    max_new_tokens=2048,
+    use_cache=True)[0]
+
+print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip())
+```
+
+## Prompt Format
+The model follow the ChatML standard, however, without `\n` at the end of `<|im_end|>`:
+```
+<|im_start|>system
+Answer the question<|im_end|><|im_start|>user
+<image>
+What is the picture about?<|im_end|><|im_start|>assistant
+```
+
+---
+| Image                                | Example                                                                                     |
+|--------------------------------------|---------------------------------------------------------------------------------------------|
+| ![small](example_1.png)              | **What is the text saying?** <br> "Small but mighty". <br>**How does the text correlate to the context of the image?** <br> The text seems to be a playful or humorous representation of a small but mighty figure, possibly a mouse or a mouse toy, holding a weightlifting bar. |
+---