Visual Question Answering
Transformers
Safetensors
English
Chinese
minicpmv
feature-extraction
custom_code
Eval Results
Instructions to use openbmb/MiniCPM-V-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V-2 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-V-2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from openbmb/MiniCPM-V-2: direct link, hf CLI and curl.
- Browser
- Download file 111 Bytes
-
https://huggingface.co/openbmb/MiniCPM-V-2/resolve/refs%2Fpr%2F13/generation_config.json
- Command line
-
hf download hf://openbmb/MiniCPM-V-2@refs/pr/13/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/openbmb/MiniCPM-V-2/resolve/refs%2Fpr%2F13/generation_config.json
111 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "transformers_version": "4.36.0" | |
| } | |