Evaluation

You can get the pretrained weight form Hugging Face Hub: turing-motors/heron-chat-git-ja-stablelm-base-7b-v0 See also notebooks .

import requests
from PIL import Image

import torch
from transformers import AutoProcessor
from heron.models.git_llm.git_llama import GitLlamaForCausalLM

device_id = 0

# prepare a pretrained model
model = GitLlamaForCausalLM.from_pretrained('turing-motors/heron-chat-git-ja-stablelm-base-7b-v0')
model.eval()
model.to(f"cuda:{device_id}")

# prepare a processor
processor = AutoProcessor.from_pretrained('turing-motors/heron-chat-git-ja-stablelm-base-7b-v0')

# prepare inputs
url = "https://www.barnorama.com/wp-content/uploads/2016/12/03-Confusing-Pictures.jpg"
image = Image.open(requests.get(url, stream=True).raw)

text = f"##Instruction: Please answer the following question concretely. ##Question: What is unusual about this image? Explain precisely and concretely what he is doing? ##Answer: "

# do preprocessing
inputs = processor(
   text,
   image,
   return_tensors="pt",
   truncation=True,
)
inputs = {k: v.to(f"cuda:{device_id}") for k, v in inputs.items()}

# set eos token
eos_token_id_list = [
   processor.tokenizer.pad_token_id,
   processor.tokenizer.eos_token_id,
]

# do inference
with torch.no_grad():
   out = model.generate(**inputs, max_length=256, do_sample=False, temperature=0., eos_token_id=eos_token_id_list)

# print result
print(processor.tokenizer.batch_decode(out))