Feature Extraction
Transformers
Safetensors
OpenVINO
minicpmo
minicpm-o
tiny-random
optimum-intel
custom_code
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("umaimaparveennineteen/tiny-random-MiniCPM-o-2_6", trust_remote_code=True, device_map="auto")Quick Links
Tiny Random MiniCPM-o-2.6
This is a tiny, randomly initialized version of the MiniCPM-o-2.6 model, designed specifically for CI/CD testing and integration validation in optimum-intel.
Model Details
- Weight Size: 5.47 MB
- Task: image-text-to-text (Visual Causal LM)
- Use Case: This model is intended for testing OpenVINO export and inference pipelines without the overhead of the full-scale model weights.
How to use
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "umaimaparveennineteen/tiny-random-MiniCPM-o-2_6"
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="umaimaparveennineteen/tiny-random-MiniCPM-o-2_6", trust_remote_code=True)