Hugging Face's logo

zjunlp
/
OceanGPT-7b-v0.2

Text Generation
Transformers
Safetensors
English
Chinese
qwen2
ocean
text-generation-inference
oceangpt
conversational
Inference Endpoints
Model card Files Community
OceanGPT-7b-v0.2
File size: 4,546 Bytes 
8895aa0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4a6061e
8895aa0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
 
---
license: mit
pipeline_tag: text-generation
tags:
- ocean
- text-generation-inference
- oceangpt
language:
- en
datasets:
- zjunlp/OceanBench
---

<div align="center">
<img src="logo.jpg" width="300px">

**OceanGPT: A Large Language Model for Ocean Science Tasks**

<p align="center">
  <a href="https://github.com/zjunlp/OceanGPT">Project</a> •
  <a href="https://arxiv.org/abs/2310.02031">Paper</a> •
  <a href="https://huggingface.co/collections/zjunlp/oceangpt-664cc106358fdd9f09aa5157">Models</a> •
  <a href="http://oceangpt.zjukg.cn/#model">Web</a> •
  <a href="#quickstart">Quickstart</a> •
  <a href="#citation">Citation</a>
</p>


</div>

OceanGPT-7b-v0.2 is based on Qwen2 and has been trained on a bilingual dataset in the ocean domain, covering both Chinese and English.


## ⏩Quickstart
### Download the model

Download the model: [OceanGPT-7b-v0.2](https://huggingface.co/zjunlp/OceanGPT-7b-v0.2)

```shell
git lfs install
git clone https://huggingface.co/zjunlp/OceanGPT-7b-v0.2
```
or
```
huggingface-cli download --resume-download zjunlp/OceanGPT-7b-v0.2 --local-dir OceanGPT-7b-v0.2 --local-dir-use-symlinks False
```
### Inference

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
device = "cuda" # the device to load the model onto
path = 'YOUR-MODEL-PATH'
model = AutoModelForCausalLM.from_pretrained(
    path,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(path)

prompt = "Which is the largest ocean in the world?"
messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
```

## 📌Models

| Model Name        | HuggingFace                                                          | WiseModel                                                                 | ModelScope                                                                |
|-------------------|-----------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------|
| OceanGPT-14B-v0.1 (based on Qwen) | <a href="https://huggingface.co/zjunlp/OceanGPT-14B-v0.1" target="_blank">14B</a> | <a href="https://wisemodel.cn/models/zjunlp/OceanGPT-14B-v0.1" target="_blank">14B</a> | <a href="https://modelscope.cn/models/ZJUNLP/OceanGPT-14B-v0.1" target="_blank">14B</a> |
| OceanGPT-7B-v0.2 (based on Qwen) | <a href="https://huggingface.co/zjunlp/OceanGPT-7b-v0.2" target="_blank">7B</a>   | <a href="https://wisemodel.cn/models/zjunlp/OceanGPT-7b-v0.2" target="_blank">7B</a>   | <a href="https://modelscope.cn/models/ZJUNLP/OceanGPT-7b-v0.2" target="_blank">7B</a>   |
| OceanGPT-2B-v0.1 (based on MiniCPM) | <a href="https://huggingface.co/zjunlp/OceanGPT-2B-v0.1" target="_blank">2B</a>   | <a href="https://wisemodel.cn/models/zjunlp/OceanGPT-2b-v0.1" target="_blank">2B</a>   | <a href="https://modelscope.cn/models/ZJUNLP/OceanGPT-2B-v0.1" target="_blank">2B</a>   |
| OceanGPT-V  | To be released                                                                    | To be released                                                                         | To be released                                                                          |
---

## 🌻Acknowledgement

OceanGPT is trained based on the open-sourced large language models including [Qwen](https://huggingface.co/Qwen), [MiniCPM](https://huggingface.co/collections/openbmb/minicpm-2b-65d48bf958302b9fd25b698f), [LLaMA](https://huggingface.co/meta-llama). Thanks for their great contributions!


### 🚩Citation

Please cite the following paper if you use OceanGPT in your work.

```bibtex
@article{bi2023oceangpt,
  title={OceanGPT: A Large Language Model for Ocean Science Tasks},
  author={Bi, Zhen and Zhang, Ningyu and Xue, Yida and Ou, Yixin and Ji, Daxiong and Zheng, Guozhou and Chen, Huajun},
  journal={arXiv preprint arXiv:2310.02031},
  year={2023}
}

```