Visual Question Answering
Transformers
Safetensors
minicpmv
feature-extraction
custom_code
4-bit precision
bitsandbytes
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
Fix task tag
#9 opened almost 2 years ago
by
merve
What framework do you use to quantize this model?
#8 opened about 2 years ago
by
sipie800
I would like to get the embedding vector as ouput. Is it supported?
2
#7 opened about 2 years ago
by
iwonder87
Fix task name
#6 opened over 2 years ago
by
merve
Logits Extraction
1
#5 opened over 2 years ago
by
Romnags
can we use lora to finetuning this int4 model?
1
#3 opened over 2 years ago
by
khangnh
report for local try run
2
#2 opened over 2 years ago
by
kennyx
Look forward to the GGUF version of this model
❤️ 5
7
#1 opened over 2 years ago
by
jian2023