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https://github.com/rasbt/LLMs-from-scratch.git
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update pr
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parent
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@ -38,7 +38,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch version: 2.2.1\n"
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"torch version: 2.2.2\n"
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]
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}
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],
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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_in*num_heads, d_out*num_heads)\n",
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" self.out_proj = nn.Linear(d_out*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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@ -365,6 +365,14 @@
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"\n",
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"print(\"context_vecs.shape:\", context_vecs.shape)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f1d965a5-9b98-4554-8646-7ecd497874cb",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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@ -383,7 +391,7 @@
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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": "3.12.3"
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"version": "3.11.4"
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}
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},
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"nbformat": 4,
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@ -341,7 +341,7 @@
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" self.d_out = d_out\n",
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"\n",
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" self.qkv = nn.Linear(d_in, 3 * d_out, bias=qkv_bias)\n",
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" self.proj = nn.Linear(d_in, d_out)\n",
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" self.proj = nn.Linear(d_out, d_out)\n",
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" self.dropout = dropout\n",
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"\n",
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" def forward(self, x):\n",
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