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---
license: apache-2.0
language:
- en
---
<h1 align="center">UForm</h1>
<h3 align="center">
Pocket-Sized Multimodal AI<br/>
For Content Understanding and Generation<br/>
</h3>
## Description
UForm-Gen is a small generative vision-language model primarily designed for Image Captioning and Visual Question Answering. The model consists of two parts:
1. [UForm Vision Encoder](https://huggingface.co/unum-cloud/uform-vl-english)
2. [Sheared-LLaMA-1.3B](https://huggingface.co/princeton-nlp/Sheared-LLaMA-1.3B) manually tuned on the instructions dataset
The model was pre-trained on: MSCOCO, SBU Captions, Visual Genome, VQAv2, GQA and a few internal datasets. UForm-Gen-Chat is SFT version of [`UForm-Gen`](https://huggingface.co/unum-cloud/uform-gen) for multimodal chat.
### Usage
```bash
pip install uform
```
```python
from uform.gen_model import VLMForCausalLM, VLMProcessor
model = VLMForCausalLM.from_pretrained("unum-cloud/uform-gen-chat")
processor = VLMProcessor.from_pretrained("unum-cloud/uform-gen-chat")
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "<image> {Your message}"}
]
image = processor.image_processor(Image.open("zebra.jpg")).unsqueeze(0)
input_ids = processor.tokenizer.apply_chat_template(
messages, return_tensors="pt", add_generation_prompt=True
)
attention_mask = torch.ones(1, input_ids.shape[1] + processor.num_image_latents - 1)
inputs = {
"input_ids": input_ids,
"attention_mask": attention_mask,
"images": image,
}
outputs = model.generate(
**inputs,
do_sample=False,
use_cache=True,
max_new_tokens=1024,
eos_token_id=32001,
pad_token_id=processor.tokenizer.pad_token_id,
)
message = processor.batch_decode(outputs[:, inputs["input_ids"].shape[1]:-1])
```
## Evaluation
For captioning evaluation we measure CLIPScore and RefCLIPScore¹.
| Model | Size | Caption Length | CLIPScore | RefCLIPScore |
| :---------------------------------- | ---: | -------------: | --------: | -----------: |
| `llava-hf/llava-1.5-7b-hf` | 7B | Long | 0.878 | 0.529 |
| `llava-hf/llava-1.5-7b-hf` | 7B | Short | 0.886 | 0.531 |
| |
| `Salesforce/instructblip-vicuna-7b` | 7B | Long | 0.902 | 0.534 |
| `Salesforce/instructblip-vicuna-7b` | 7B | Short | 0.848 | 0.523 |
| | |
| `unum-cloud/uform-gen-chat` | 1.5B | Long | 0.860 | 0.525 |
| `unum-cloud/uform-gen-chat` | 1.5B | Short | 0.858 | 0.525 |
¹ We used `apple/DFN5B-CLIP-ViT-H-14-378` CLIP model. |