Any-to-Any
Transformers
Safetensors
multilingual
minicpmo
feature-extraction
minicpm-o
omni
vision
ocr
multi-image
video
custom_code
audio
speech
voice cloning
live Streaming
realtime speech conversation
asr
tts
4-bit precision
gptq
Instructions to use openbmb/MiniCPM-o-2_6-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-o-2_6-GPTQ with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-o-2_6-GPTQ", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download quantize_config.json from openbmb/MiniCPM-o-2_6-GPTQ: direct link, hf CLI and curl.
- Browser
- Download file 348 Bytes
-
https://huggingface.co/openbmb/MiniCPM-o-2_6-GPTQ/resolve/main/quantize_config.json
- Command line
-
hf download hf://openbmb/MiniCPM-o-2_6-GPTQ/quantize_config.json
-
curl -L -o quantize_config.json https://huggingface.co/openbmb/MiniCPM-o-2_6-GPTQ/resolve/main/quantize_config.json
348 Bytes
| { | |
| "bits": 4, | |
| "group_size": 128, | |
| "damp_percent": 0.01, | |
| "desc_act": false, | |
| "static_groups": false, | |
| "sym": true, | |
| "true_sequential": true, | |
| "model_name_or_path": "/cache/shitong/autoGPTQ/models/MiniCPM-o-2_6-gptq-int4/_llm_temp", | |
| "model_file_base_name": "gptq_model-4bit-128g", | |
| "quant_method": "gptq", | |
| "checkpoint_format": "gptq" | |
| } |