metadata
license: cc
language:
- en
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
todos:
- check numerical output same as original VILA impl
- check training stablitiy
- save_pretrained()
already finished
- AutoModel.from_pretrained() / device_map auto to shard
- loading
- fix recursive imports
- text conv
- image + text conv:
- .generate() / .generate_content()
- llava/cli/infer.py
- tests/bash/test_inference.sh
NVILA HF Comptatible Mode
Remote model loading example
from transformers import AutoConfig, AutoModel
from termcolor import colored
model_path = "Efficient-Large-Model/nvila_lite_3b_dev"
print("main_dev.py, loading from ", model_path)
# config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
# model = AutoModel.from_config(config, trust_remote_code=True)
model = AutoModel.from_pretrained(model_path, trust_remote_code=True, device_map="auto")
res = model.generate_content([
"how are you today?"
])
print(colored(res, "cyan", attrs=["bold"]))
print("---" * 40)
import PIL.Image
response = model.generate_content([
PIL.Image.open("inference_test/test_data/caption_meat.jpeg"),
"describe the image?"
])
print(colored(response, "cyan", attrs=["bold"]))