|
--- |
|
license: other |
|
license_name: tongyi-qianwen |
|
base_model: Qwen/Qwen2-72B |
|
tags: |
|
- generated_from_trainer |
|
- axolotl |
|
datasets: |
|
- cognitivecomputations/Dolphin-2.9 |
|
- teknium/OpenHermes-2.5 |
|
- m-a-p/CodeFeedback-Filtered-Instruction |
|
- cognitivecomputations/dolphin-coder |
|
- cognitivecomputations/samantha-data |
|
- microsoft/orca-math-word-problems-200k |
|
- Locutusque/function-calling-chatml |
|
- internlm/Agent-FLAN |
|
--- |
|
|
|
# DolphinVision 72b 🐬 |
|
|
|
Curated and trained by Quan Nguyen (qnguyen3/stablequan), Eric Hartford, and Cognitive Computations |
|
|
|
[](https://discord.gg/h3K4XGj2RH) |
|
Discord: https://discord.gg/h3K4XGj2RH |
|
|
|
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/DBGu4dJ95RHHN3yOEuXuP.png" width="600" /> |
|
|
|
Our appreciation for the sponsors of DolphinVision: |
|
- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xH100 node used for training |
|
- [TensorWave](https://tensorwave.com/) - provided 8x mi300x node used for evaluations and inference |
|
|
|
DolphinVision is a multimodal model. It is uncensored, and capable to reason and comment regarding images that other popular models would object to. |
|
|
|
|
|
```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 = 'cognitivecomputations/dolphin-vision-72b' |
|
|
|
# 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()) |
|
``` |
|
|
|
## Examples |
|
|
|
 |
|
``` |
|
<|im_start|>user |
|
: do OCR on all the text |
|
<|im_start|>assistant |
|
: The text in the image reads as follows: |
|
|
|
- STOP USING DOCKER |
|
- Applications were not meant to be trapped in virtual jars like digital fireflies |
|
- Years of software development, yet no one questioned why we were putting programs in imaginary boats |
|
- Let's containerize our monolith. I'll just quickly spin up 17 microservices. Statements dreamt up by the utterly deranged |
|
- Observe the whale-sized deception they fooled us with all this time |
|
- These are real images used to explain Docker |
|
- "Yay Matey, I'd like to run my website in a virtual sea" |
|
- They have played us for absolute fools |
|
|
|
This text is a satirical commentary on the use of Docker in software development, using humor and exaggeration to question the practice. |
|
``` |
|
|
|
## Benchmarks |
|
|
|
| Model | **VQA v2** | **MMBench** | **MMMU (Eval)** | **MathVista** | **RealWorldQA** | |
|
|---------|--------|---------|------------|------|--------| |
|
| Dolphin-Vision-72B | 83.6 | 81.2 | 45.7| 47.25| 66.4 | |
