Update README.md
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README.md
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README.md
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@ -6,6 +6,8 @@ Besides the usual **FP32**, it supports **FP16** and **quantized INT4** inferenc
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RWKV is a novel large language model architecture, [with the largest model in the family having 14B parameters](https://huggingface.co/BlinkDL/rwkv-4-pile-14b). In contrast to Transformer with `O(n^2)` attention, RWKV requires only state from previous step to calculate logits. This makes RWKV very CPU-friendly on large context lenghts.
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RWKV is a novel large language model architecture, [with the largest model in the family having 14B parameters](https://huggingface.co/BlinkDL/rwkv-4-pile-14b). In contrast to Transformer with `O(n^2)` attention, RWKV requires only state from previous step to calculate logits. This makes RWKV very CPU-friendly on large context lenghts.
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This project provides [a C library rwkv.h](rwkv.h) and [a convinient Python wrapper](rwkv%2Frwkv_cpp_model.py) for it.
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**TODO**:
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**TODO**:
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1. Measure performance and perplexity of different model sizes and data types
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1. Measure performance and perplexity of different model sizes and data types
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python rwkv\convert_pytorch_rwkv_to_ggml.py C:\RWKV-4-Pile-169M-20220807-8023.pth C:\rwkv.cpp-169M.bin float32
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python rwkv\convert_pytorch_rwkv_to_ggml.py C:\RWKV-4-Pile-169M-20220807-8023.pth C:\rwkv.cpp-169M.bin float32
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```
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```
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#### 2.1. Optionally, quantize the model
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To convert the model into INT4 quantized format, run:
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```commandline
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python rwkv\quantize.py C:\rwkv.cpp-169M.bin C:\rwkv.cpp-169M-Q4_1.bin 3
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```
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Pass `2` for `Q4_0` format (smaller size, lower quality), `3` for `Q4_1` format (larger size, higher quality).
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### 3. Run the model
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### 3. Run the model
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**Requirements**: Python 3.x with [PyTorch](https://pytorch.org/get-started/locally/) and [tokenizers](https://pypi.org/project/tokenizers/).
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**Requirements**: Python 3.x with [PyTorch](https://pytorch.org/get-started/locally/) and [tokenizers](https://pypi.org/project/tokenizers/).
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