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@@ -228,7 +228,7 @@
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" [CausalSelfAttention(d_in, d_out, context_length, dropout, qkv_bias) \n",
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" for _ in range(num_heads)]\n",
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" )\n",
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- " self.out_proj = nn.Linear(d_out*num_heads, d_out*num_heads)\n",
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+ " self.out_proj = nn.Linear(d_in*num_heads, d_out*num_heads)\n",
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"\n",
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" def forward(self, x):\n",
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" context_vec = torch.cat([head(x) for head in self.heads], dim=-1)\n",
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@@ -383,7 +383,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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- "version": "3.11.4"
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+ "version": "3.12.3"
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}
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},
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"nbformat": 4,
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