nvila_lite_2b_dev-model

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"]))