metadata
language:
- ja
tags:
- heron
- vision
- image-captioning
- VQA
pipeline_tag: image-to-text
license:
- apache-2.0
inference: false
Heron BLIP Japanese StableLM Base 7B
Model Details
Heron BLIP 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 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', additional_special_tokens=["▁▁"])
# 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 concletely. ##Question: What is unusual about this image? Explain precisely and concletely 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))
Model Details
- Developed by: Turing Inc.
- Adaptor type: BLIP2
- Lamguage Model: Japanese StableLM Base Alpha
- Language(s): Japanese
- License: This model is licensed under Apache License, Version 2.0.
Training
This model was initially trained with the Adaptor using STAIR Captions. In the second phase, it was fine-tuned with LLaVA-Instruct-150K-JA and Japanese Visual Genome using LoRA.
Training Dataset
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{GitJapaneseStableLM,
url = {[https://huggingface.co/turing-motors/heron-chat-blip-ja-stablelm-base-7b-v0](https://huggingface.co/turing-motors/heron-chat-blip-ja-stablelm-base-7b-v0)},
title = {Heron BLIP Japanese StableLM Base 7B},
author = {Kotaro Tanahashi, Yuichi Inoue, and Yu Yamaguchi}
}
Citations
@misc{JapaneseInstructBLIPAlpha,
url = {[https://huggingface.co/stabilityai/japanese-instructblip-alpha](https://huggingface.co/stabilityai/japanese-instructblip-alpha)},
title = {Japanese InstructBLIP Alpha},
author = {Shing, Makoto and Akiba, Takuya}
}