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"]))
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