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README.md
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---
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language: en
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license: mit
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library_name: transformers
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tags:
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- text-generation
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- shakespeare
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- transformer
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- pytorch
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pipeline_tag: text-generation
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model_type: kimi-k2
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---
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# nanokimi-mini
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This repository contains a nanoKimi model checkpoint trained on Shakespeare dataset.
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## Model Details
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- **Architecture**: 12 layers, 12 heads, 768 embedding dimension
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- **Training Data**: Shakespeare dataset
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- **Features**: Mixture of Experts (8 experts), Latent Attention
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- **Model Type**: Kimi-K2 (custom transformer)
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## Files
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- `pytorch_model.bin` - Model weights
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- `config.json` - Model configuration
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- `src/` - Source code for model architecture
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- `modeling_kimik2.py` - HuggingFace wrapper
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## Usage
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```python
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import torch
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import json
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from huggingface_hub import hf_hub_download
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# Download files
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config_path = hf_hub_download(repo_id="sohv/nanokimi-mini", filename="config.json")
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weights_path = hf_hub_download(repo_id="sohv/nanokimi-mini", filename="pytorch_model.bin")
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# Load config and weights
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with open(config_path) as f:
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config = json.load(f)
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weights = torch.load(weights_path, map_location="cpu")
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print("Model downloaded successfully!")
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```
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## License
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MIT License
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