|
--- |
|
license: mit |
|
--- |
|
|
|
**TLDR**: We trained a Flamingo with Llama2-Chat7B as LLM on CC3M in less than 5 hours using just 4 A100s. |
|
|
|
The model showed promising zero-shot captioning skills. High-quality captioning data really helps fast alignment. |
|
|
|
You could test it via following code. Be sure to visit [Otter](https://github.com/Luodian/Otter) to get necessary Flamingo/Otter models. |
|
|
|
```python |
|
from flamingo.modeling_flamingo import FlamingoForConditionalGeneration |
|
flamingo_model = FlamingoForConditionalGeneration.from_pretrained("luodian/Flamingo-Llama2-Chat7B-CC3M", device_map=auto) |
|
prompt = "<image>an image of" |
|
simple_prompt = "<image>" |
|
``` |
