Model reference · open weights
uform-gen2-qwen is an open-weight language model from unum-cloud. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | unum-cloud |
|---|---|
| Type | Language models |
| Task | Image→text |
| Parameters (lead) | 1.3B |
| Runs with | transformers |
| Released | 2024-02-15 |
| Popularity | 510 downloads / month |
| Licence | Open weights |
About
Pocket-Sized Multimodal AI For Content Understanding and Generation
UForm-Gen is a small generative vision-language model primarily designed for Image Captioning and Visual Question Answering. The model consists of two parts:
The model was pre-trained on the internal image captioning dataset and fine-tuned on public instructions datasets: SVIT, LVIS, VQAs datasets. The model took one day to train on a DGX-H100 with 8x H100 GPUs. Thanks to Nebius.ai for providing the compute 🤗
The generative model can be used to caption images, answer questions about them. Also it is suitable for a multimodal chat.
from transformers import AutoModel, AutoProcessor
model = AutoModel.from_pretrained("unum-cloud/uform-gen2-qwen-500m", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("unum-cloud/uform-gen2-qwen-500m", trust_remote_code=True)
prompt = "Question or Instruction"
image = Image.open("image.jpg")
inputs = processor(text=[prompt], images=[image], return_tensors="pt")
with torch.inference_mode():
output = model.generate(
**inputs,
do_sample=False,
use_cache=True,
max_new_tokens=256,
eos_token_id=151645,
pad_token_id=processor.tokenizer.pad_token_id
)
prompt_len = inputs["input_ids"].shape[1]
decoded_text = processor.batch_decode(output[:, prompt_len:])[0]
You can check examples of different prompts in our demo space.
| Model | LLM Size | SQA | MME | MMBench | Average¹ |
|---|---|---|---|---|---|
| UForm-Gen2-Qwen-500m | 0.5B | 45.5 | 880.1 | 42.0 | 29.31 |
| MobileVLM v2 | 1.4B | 52.1 | 1302.8 | 57.7 | 36.81 |
| LLaVA-Phi | 2.7B | 68.4 | 1335.1 | 59.8 | 42.95 |
¹MME scores were divided by 2000 before averaging.
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys uform-gen2-qwen for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (uform-gen2-qwen below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"uform-gen2-qwen","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.