Instructions to use openbmb/MiniCPM-Llama3-V-2_5-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-Llama3-V-2_5-int4 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-Llama3-V-2_5-int4", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-Llama3-V-2_5-int4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Look forward to the GGUF version of this model
Maybe it can be used in ollama
Currently using the v2 gguf, though this is a significant improvement and having a gguf of this would be greatly appreciated.
The strong OCR abilities of this model would be very helpful for making documents accessible.
This model is excellent and all your kind efforts and contributions to the community are greatly appreciated.
The GGUF format will be released soon😃
Thank you all for the valuable feedback! We really appreciate it. We are working on GGUF and ollama for MiniCPM-Llama3-V 2.5, which will be available soon. We hope the model can help the community and the people in need.
MiniCPM-Llama3-V 2.5 can run with llama.cpp now! See our fork of llama.cpp for more detail.
and here is our model in gguf format.
https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-gguf
@ibrahimkettaneh
We have supported Ollama! Please visit our GitHub for more usage info! https://github.com/OpenBMB/MiniCPM-V