e52be9bba2
Deepseek V2 is a MoE model from Deepseek. Relevant variations
compared to other models:
- Grouped top-K in expert selection.
- mscale in yarn is calculated using the `mscale` and `mscale_all_dim`
configuration options.
- `mscale_all_dim` is also used in scaling attention softmax.
- Permuting of the query/key representations before applying rotary
embeddings.
- Some projections cannot be sharded (`q_a_proj`, `kv_a_proj_with_mqa`).
So, we need weight loads that supports quantized weights. To this
end `{Weights,WeightLoader}.get_weight` was added.
- The query/key head dimensionality differs from that of the value,
so we need to pad during attention.
- Heads with size 192, needs an extension to our paged attention
fork and we need to ensure that the KV cache is allocated with the
correct size.
- Shared experts.
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|---|---|---|
| .. | ||
| custom_kernels | ||
| exllama_kernels | ||
| exllamav2_kernels | ||
| marlin | ||
| tests | ||
| text_generation_server | ||
| .gitignore | ||
| Makefile | ||
| Makefile-awq | ||
| Makefile-eetq | ||
| Makefile-flash-att | ||
| Makefile-flash-att-v2 | ||
| Makefile-lorax-punica | ||
| Makefile-selective-scan | ||
| Makefile-vllm | ||
| README.md | ||
| poetry.lock | ||
| pyproject.toml | ||
| requirements_cuda.txt | ||
| requirements_intel.txt | ||
| requirements_rocm.txt | ||
README.md
Text Generation Inference Python gRPC Server
A Python gRPC server for Text Generation Inference
Install
make install
Run
make run-dev