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Qwen
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QwQ-32B

Text Generation
Transformers
Safetensors
English
qwen2
chat
conversational
text-generation-inference
Inference Endpoints
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docs: update README.md

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Paramaters -> Parameters

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  1. README.md +1 -1
README.md CHANGED
@@ -30,7 +30,7 @@ QwQ is the reasoning model of the Qwen series. Compared with conventional instru
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  - Training Stage: Pretraining & Post-training (Supervised Finetuning and Reinforcement Learning)
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  - Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
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  - Number of Parameters: 32.5B
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- - Number of Paramaters (Non-Embedding): 31.0B
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  - Number of Layers: 64
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  - Number of Attention Heads (GQA): 40 for Q and 8 for KV
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  - Context Length: Full 131,072 tokens
 
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  - Training Stage: Pretraining & Post-training (Supervised Finetuning and Reinforcement Learning)
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  - Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
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  - Number of Parameters: 32.5B
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+ - Number of Parameters (Non-Embedding): 31.0B
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  - Number of Layers: 64
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  - Number of Attention Heads (GQA): 40 for Q and 8 for KV
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  - Context Length: Full 131,072 tokens