deepgeek/MiniCPM-o
2
0
Fork 0
mirror of https://github.com/OpenBMB/MiniCPM-V.git synced 2026-02-05 02:09:20 +08:00
Code Issues Packages Projects Releases Wiki Activity

update readme

Browse Source
This commit is contained in:
yiranyyu
2024-05-23 11:25:30 +08:00
parent 96b9bca796
commit ef2b191f25
2 changed files with 5 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
README.md
View File

@@ -25,6 +25,7 @@
## News <!-- omit in toc -->
<!-- * [2024.05.22] We further improved the inference efficiency on edge-side devices, providing a speed of 6-8 tokens/s, try it now! -->
* [2024.05.20] We open-soure MiniCPM-Llama3-V 2.5, it has improved OCR capability and supports 30+ languages, representing the first edge-side multimodal LLM achieving GPT-4V level performance! We provide [efficient inference](#deployment-on-mobile-phone) and [simple fine-tuning](./finetune/readme.md), try it now!
* [2024.04.23] MiniCPM-V-2.0 supports vLLM now! Click [here](#vllm) to view more details.
* [2024.04.18] We create a HuggingFace Space to host the demo of MiniCPM-V 2.0 at [here](https://huggingface.co/spaces/openbmb/MiniCPM-V-2)!
@@ -462,7 +463,7 @@ pip install -r requirements.txt
| MiniCPM-V 1.0 | Lightest version, achieving the fastest inference. | [🤗](https://huggingface.co/openbmb/MiniCPM-V) &nbsp;&nbsp; [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V) |
### Multi-turn Conversation
Please refer to the following codes to run `MiniCPM-V` and `OmniLMM`.
Please refer to the following codes to run `MiniCPM-V`
<div align="center">
<img src="assets/airplane.jpeg" width="500px">
@@ -618,9 +619,9 @@ Please contact cpm@modelbest.cn to obtain written authorization for commercial u
## Statement <!-- omit in toc -->
As LMMs, OmniLMMs generate contents by learning a large amount of multimodal corpora, but they cannot comprehend, express personal opinions or make value judgement. Anything generated by OmniLMMs does not represent the views and positions of the model developers
As LMMs, MiniCPM-V models (including OmniLMM) generate contents by learning a large amount of multimodal corpora, but they cannot comprehend, express personal opinions or make value judgement. Anything generated by MiniCPM-V models does not represent the views and positions of the model developers
We will not be liable for any problems arising from the use of OmniLMM open source models, including but not limited to data security issues, risk of public opinion, or any risks and problems arising from the misdirection, misuse, dissemination or misuse of the model.
We will not be liable for any problems arising from the use of MiniCPMV-V models, including but not limited to data security issues, risk of public opinion, or any risks and problems arising from the misdirection, misuse, dissemination or misuse of the model.
## Institutions <!-- omit in toc -->