Heron GIT Japanese StableLM Base 7B
Model Details
Heron GIT Japanese StableLM Base 7B is a vision-language model that can converse about input images.
This model was trained using the heron library. Please refer to the code for details.
Usage
Follow the installation guide.
import torch
from heron.models.git_llm.git_japanese_stablelm_alpha import GitJapaneseStableLMAlphaForCausalLM
from transformers import AutoProcessor, LlamaTokenizer
device_id = 0
device = f"cuda:{device_id}"
MODEL_NAME = "turing-motors/heron-chat-git-ja-stablelm-base-7b-v1"
model = GitJapaneseStableLMAlphaForCausalLM.from_pretrained(
MODEL_NAME, torch_dtype=torch.float16, ignore_mismatched_sizes=True
)
model.eval()
model.to(device)
# prepare a processor
processor = AutoProcessor.from_pretrained(MODEL_NAME)
tokenizer = LlamaTokenizer.from_pretrained(
"novelai/nerdstash-tokenizer-v1",
padding_side="right",
additional_special_tokens=["▁▁"],
)
processor.tokenizer = tokenizer
import requests
from PIL import Image
# 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"##human: この画像の面白い点は何ですか?\n##gpt: "
# do preprocessing
inputs = processor(
text=text,
images=image,
return_tensors="pt",
truncation=True,
)
inputs = {k: v.to(device) for k, v in inputs.items()}
# do inference
with torch.no_grad():
out = model.generate(**inputs, max_length=256, do_sample=False, temperature=0., no_repeat_ngram_size=2)
# print result
print(processor.tokenizer.batch_decode(out))
Model Details
- Developed by: Turing Inc.
- Adaptor type: GIT
- Lamguage Model: Japanese StableLM Base Alpha
- Language(s): Japanese
Training
- The GIT adaptor was trained with LLaVA-Pratrain-JA.
- The LLM and the adapter were fully fine-tuned with LLaVA-Instruct-620K-JA-v2.
Training Dataset
- LLaVA-Pratrain-JA
- LLaVA-Instruct-620K-JA-v2
Use and Limitations
Intended Use
This model is intended for use in chat-like applications and for research purposes.
Limitations
The model may produce inaccurate or false information, and its accuracy is not guaranteed. It is still in the research and development stage.
How to cite
@misc{inoue2024heronbench,
title={Heron-Bench: A Benchmark for Evaluating Vision Language Models in Japanese},
author={Yuichi Inoue and Kento Sasaki and Yuma Ochi and Kazuki Fujii and Kotaro Tanahashi and Yu Yamaguchi},
year={2024},
eprint={2404.07824},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
license: cc-by-nc-4.0
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