Heron Chat Git Llama 2 7b V0

🚀 Heron GIT Llama 2 Fast 7B

Heron GIT Llama 2 7B 是一款视觉语言模型，能够针对输入的图像进行对话交流，为图像理解和交互提供了强大的支持。

🚀 快速开始

请按照 安装指南 进行操作。

💻 使用示例

基础用法

import requests
from PIL import Image

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

device_id = 0

# prepare a pretrained model
model = GitLlamaForCausalLM.from_pretrained(
    'turing-motors/heron-chat-git-Llama-2-7b-v0', torch_dtype=torch.float16
)
model.eval()
model.to(f"cuda:{device_id}")

# prepare a processor
processor = AutoProcessor.from_pretrained('turing-motors/heron-chat-git-Llama-2-7b-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"##human: What is this picture?\n##gpt: "

# 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)[0])

📚 详细文档

模型详情

Heron GIT Llama 2 7B 是一个能够对输入图像进行对话的视觉语言模型。该模型使用 heron 库 进行训练，具体细节请参考代码。

训练过程

此模型最初使用 Adaptor 在 M3IT 中的 Coco Captions 上进行训练。第二阶段，使用 M3IT 进行微调。最后，通过使用 LLaVA - Instruct - 150K 进行指令调优训练。

训练数据集

• LLaVA-Instruct-150K
• M3IT

🔧 使用与限制

预期用途

该模型旨在用于类似聊天的应用程序以及研究目的。

局限性

该模型可能会产生不准确或错误的信息，其准确性无法保证，目前仍处于研发阶段。

📄 许可证

本项目采用 cc-by-nc-4.0 许可证。

🔖 引用方式

@misc{GitLlama2, 
    url    = {[https://huggingface.co/turing-motors/heron-chat-git-Llama-2-7b-v0](https://huggingface.co/turing-motors/heron-chat-git-Llama-2-7b-v0)}, 
    title  = {Heron GIT Llama 2 7B}, 
    author = {Yuichi Inoue, Kotaro Tanahashi, and Yu Yamaguchi}
}

相关引用

@misc{touvron2023llama,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models}, 
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}