File size: 1,342 Bytes
f49dd57
 
 
 
 
 
 
 
 
621a691
a5ff545
d9d7515
f49dd57
 
 
 
 
 
 
 
 
 
 
 
 
 
1cbe605
f49dd57
 
 
 
 
 
 
 
 
1cbe605
35a32fb
 
f49dd57
 
 
 
 
 
 
 
271378d
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
---
language:
- zh
- en
---


# ChatTruth-7B

**ChatTruth-7B** 在Qwen-VL的基础上,使用精心设计的数据进行了优化训练。与Qwen-VL相比,模型在大分辨率上得到了大幅提升。创新性提出Restore Module使大分辨率计算量大幅减少。

![image/png](https://cdn-uploads.huggingface.co/production/uploads/657bef8a5c6f0b1f36fcf28e/kwgU2AxZbJzxmgWULwv6A.png)

## 安装要求 (Requirements)

* transformers 4.32.0
* python 3.8 and above
* pytorch 1.13 and above
* CUDA 11.4 and above
  
  <br>

## 快速开始 (Quickstart)

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation import GenerationConfig
import torch
torch.manual_seed(1234)
model_path = 'ChatTruth-7B' # your downloaded model path.

tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)

# use cuda device
model = AutoModelForCausalLM.from_pretrained(model_path, device_map="cuda", trust_remote_code=True).eval()

model.generation_config = GenerationConfig.from_pretrained(model_path, trust_remote_code=True)
model.generation_config.top_p = 0.01

query = tokenizer.from_list_format([
    {'image': 'demo.jpeg'},
    {'text': '图片中的文字是什么'},
])
response, history = model.chat(tokenizer, query=query, history=None)
print(response)

# 昆明太厉害了
```