System.Numerics.Tensors 8.0.0-rc.1.23419.4
Tensor class which represents and extends multi-dimensional arrays.
Commonly Used Types:
System.Numerics.Tensors.Tensor<T>
System.Numerics.Tensors.CompressedSparseTensor<T>
System.Numerics.Tensors.DenseTensor<T>
System.Numerics.Tensors.SparseTensor<T>
Showing the top 20 packages that depend on System.Numerics.Tensors.
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LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/LLaVA model (and others) in your local device.
Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
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1 |
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LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/Mtmd model (and others) in your local device.
Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
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1 |
|
LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/Mtmd model (and others) in your local device.
Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
|
3 |
https://go.microsoft.com/fwlink/?LinkID=799421
.NET Framework 4.6.2
- System.Memory (>= 4.5.5)
.NET 6.0
- No dependencies.
.NET 7.0
- No dependencies.
.NET 8.0
- No dependencies.
.NET Standard 2.0
- System.Memory (>= 4.5.5)