llama : add Command R Plus support (#6491)
* Add Command R Plus GGUF * Add Command R Plus GGUF * Loading works up to LayerNorm2D * Export new tensors in 1D so they are not quantized. * Fix embedding layer based on Noeda's example * Whitespace * Add line * Fix unexpected tokens on MPS. Re-add F16 fix. ((Noeda) * dranger003: Fix block index overflow in CUDA dequantizing. * Reverted blocked multiplication code as it still has issues and could affect other Llama arches * export norms as f32 * fix overflow issues during quant and other cleanup * Type convention Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * dranger003: Fix more int overflow during quant. --------- Co-authored-by: S <seast@Ss-Mac-Studio.local> Co-authored-by: S <s@example.com> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -1225,7 +1225,7 @@ static void ggml_cuda_op_mul_mat_cublas(
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// the main device has a larger memory buffer to hold the results from all GPUs
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// ldc == nrows of the matrix that cuBLAS writes into
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int ldc = id == ctx.device ? ne0 : row_diff;
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int64_t ldc = id == ctx.device ? ne0 : row_diff;
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const int compute_capability = ggml_cuda_info().devices[id].cc;
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@ -1377,8 +1377,8 @@ static void ggml_cuda_op_mul_mat(
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const int64_t ne0 = dst->ne[0];
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const int64_t ne1 = dst->ne[1];
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const int nb2 = dst->nb[2];
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const int nb3 = dst->nb[3];
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const int64_t nb2 = dst->nb[2];
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const int64_t nb3 = dst->nb[3];
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GGML_ASSERT(ggml_backend_buffer_is_cuda(dst->buffer));
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GGML_ASSERT(ggml_backend_buffer_is_cuda(src1->buffer));
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