MiniCPM-o-2_6-int4/README.md

pipeline_tag	datasets	library_name	language	tags
any-to-any	openbmb/RLAIF-V-Dataset	transformers	multilingual	minicpm-o omni vision ocr multi-image video custom_code audio speech voice cloning live Streaming realtime speech conversation asr tts

A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone

MiniCPM-o 2.6 int4

This is the int4 quantized version of MiniCPM-o 2.6.
Running with int4 version would use lower GPU memory (about 9GB).

Prepare code and install AutoGPTQ

We are submitting PR to officially support minicpm-o 2.6 inference

git clone https://github.com/OpenBMB/AutoGPTQ.git && cd AutoGPTQ
git checkout minicpmo

# install AutoGPTQ
pip install -vvv --no-build-isolation -e .

Usage of MiniCPM-o-2_6-int4

Change the model initialization part to AutoGPTQForCausalLM.from_quantized

import torch
from transformers import AutoModel, AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM

model = AutoGPTQForCausalLM.from_quantized(
    'openbmb/MiniCPM-o-2_6-int4',
    torch_dtype=torch.bfloat16,
    device="cuda:0",
    trust_remote_code=True,
    disable_exllama=True,
    disable_exllamav2=True
)
tokenizer = AutoTokenizer.from_pretrained(
    'openbmb/MiniCPM-o-2_6-int4',
    trust_remote_code=True
)

model.init_tts()

Usage reference MiniCPM-o-2_6 Usage section.