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README.md

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+---
+license: apache-2.0
+base_model: openbmb/MiniCPM-o-2_6
+tags:
+- vision
+- text-generation
+- multimodal
+- minicpm
+- tiny-model
+- testing
+- optimum-intel
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# tiny-random-MiniCPM-o-2_6
+
+A minimal, randomly initialized version of MiniCPM-o-2_6 designed for testing and development purposes. This model maintains the same architecture as the original MiniCPM-o-2_6 but with drastically reduced dimensions to create a lightweight test model.
+
+## Model Details
+
+### Model Description
+
+This is a tiny, randomly initialized version of the MiniCPM-o-2_6 multimodal model. It was created by scaling down the original model's dimensions while preserving the architecture structure. The model is intended for:
+
+- Testing and development workflows
+- Integration testing with Optimum-Intel
+- Quick prototyping and experimentation
+- CI/CD pipelines requiring lightweight models
+
+**⚠️ Important:** This model is randomly initialized and should NOT be used for production inference. It is designed solely for testing purposes.
+
+### Model Architecture
+
+The model maintains the same architecture as MiniCPM-o-2_6 but with reduced dimensions:
+
+**Language Model (LLM):**
+- `hidden_size`: 40
+- `num_hidden_layers`: 1
+- `num_attention_heads`: 4
+- `num_key_value_heads`: 2
+- `intermediate_size`: 16
+- `max_position_embeddings`: 128
+- `vocab_size`: 151,700
+
+**Vision Component:**
+- `hidden_size`: 16
+- `num_hidden_layers`: 1
+- `num_attention_heads`: 4
+- `intermediate_size`: 8
+- `patch_size`: 14
+
+**Audio/TTS Components:**
+- Audio: Disabled (`init_audio: false`)
+- TTS: Disabled (`init_tts: false`)
+
+### Model Size
+
+- **Total Parameters**: ~6.17M
+- **Model Size**: ~12.4 MB (on disk)
+- **Precision**: bfloat16
+
+## Usage
+
+### Basic Usage
+
+```python
+from transformers import AutoModel, AutoTokenizer, AutoProcessor
+import torch
+from PIL import Image
+
+# Load model and tokenizer
+model_id = "notlikejoe/tiny-random-MiniCPM-o-2_6"
+model = AutoModel.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.bfloat16)
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
+
+# Prepare inputs
+text = "Hello, how are you?"
+image = Image.new('RGB', (224, 224), color='red')  # Dummy image
+
+# Process inputs
+inputs = processor(text=text, images=image, return_tensors="pt")
+
+# Forward pass
+model.eval()
+with torch.no_grad():
+    outputs = model(**inputs)
+```
+
+### With Optimum-Intel
+
+This model is compatible with Optimum-Intel for OpenVINO optimization:
+
+```python
+from optimum.intel import OVModelForCausalLM
+from transformers import AutoTokenizer
+
+model_id = "notlikejoe/tiny-random-MiniCPM-o-2_6"
+
+# Export to OpenVINO format
+ov_model = OVModelForCausalLM.from_pretrained(
+    model_id,
+    export=True,
+    trust_remote_code=True
+)
+
+# Use for inference
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+```
+
+## Model Validation
+
+The model has been validated to ensure:
+
+✅ Model loads successfully from Hugging Face  
+✅ Config, tokenizer, and processor load correctly  
+✅ Model structure matches expected architecture  
+✅ Compatible with Optimum-Intel export  
+✅ Forward pass completes without errors  
+
+## Limitations
+
+1. **Random Initialization**: This model is randomly initialized and will not produce meaningful outputs
+2. **Reduced Dimensions**: The model dimensions are minimal and may not capture complex patterns
+3. **Testing Only**: This model is intended for testing and development, not production use
+4. **Limited Vocabulary**: The vocabulary has been reduced to 2000 entries for size optimization
+
+## Training Details
+
+This model was not trained. It is a randomly initialized, dimensionally-reduced version of MiniCPM-o-2_6 created for testing purposes.
+
+### Training Data
+
+N/A - Model is randomly initialized.
+
+## Evaluation
+
+This model is not intended for evaluation on standard benchmarks as it is randomly initialized.
+
+## Citation
+
+If you use this model, please cite the original MiniCPM-o-2_6 model:
+
+```bibtex
+@misc{minicpm-o-2_6,
+  title={MiniCPM-o-2_6},
+  author={OpenBMB},
+  year={2024},
+  howpublished={\url{https://huggingface.co/openbmb/MiniCPM-o-2_6}}
+}
+```
+
+## Model Card Contact
+
+For questions or issues related to this model, please open an issue in the repository.
+
+## License
+
+This model is licensed under the Apache 2.0 License, same as the base model.
+