mirror of
https://github.com/huggingface/text-generation-inference.git
synced 2025-05-02 15:32:13 +00:00
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.
|
||
|---|---|---|
| .. | ||
| test_flash_deepseek_v2_all_params.json | ||
| test_flash_deepseek_v2_load.json | ||
| test_flash_deepseek_v2.json | ||