* Add Arcee AFM support
* Add draft update code
* Fix linter and update URL, may still not be final
* Update src/llama-model.cpp
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
* Remote accidental blank line
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Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Adds:
* Dots1Model to convert_hf_to_gguf.py
* Computation graph code to llama-model.cpp
* Chat template to llama-chat.cpp to detect this model's template.
---
The model is called "dots.llm1" (I decided to shorten it to dots1 or
DOTS1 in the code generally) architecture.
The only models that exist as of writing of this commit that follow this
architecture are "dots.llm1.inst" and "dots.llm1.base" from here:
* https://huggingface.co/rednote-hilab/dots.llm1.inst
* https://huggingface.co/rednote-hilab/dots.llm1.base
The model architecture is a combination of Qwen and Deepseek parts, as
seen here:
ffe12627b4/src/transformers/models/dots1/modular_dots1.py
* kv-cache : avoid modifying recurrent cells when setting inputs
* kv-cache : remove inp_s_mask
It was replaced with equivalent and simpler functionality
with rs_z (the first zeroed state) and the already-existing inp_s_copy.
* kv-cache : fix non-consecutive token pos warning for recurrent models
The problem was apparently caused by how the tail cells were swapped.
* graph : simplify logic for recurrent state copies
* kv-cache : use cell without src refs for rs_z in recurrent cache
* llama-graph : fix recurrent state copy
The `state_copy` shuffle assumes everything is moved at once,
which is not true when `states_extra` is copied back to the cache
before copying the range of states between `head` and `head + n_seqs`.
This is only a problem if any of the cells in [`head`, `head + n_seqs`)
have an `src` in [`head + n_seqs`, `head + n_kv`),
which does happen when `n_ubatch > 1` in the `llama-parallel` example.
Changing the order of the operations avoids the potential overwrite
before use, although when copies are avoided (like with Mamba2),
this will require further changes.
* llama-graph : rename n_state to state_size in build_recurrent_state
This naming should reduce confusion between the state size
and the number of states.
* llama : deprecate llama_kv_self_ API
ggml-ci
* llama : allow llama_memory_(nullptr)
ggml-ci
* memory : add flag for optional data clear in llama_memory_clear
ggml-ci
* kv-cache : simplify the "struct llama_kv_cache" interface
ggml-ci
* kv-cache : revert the (n_swa + n_ubatch) change (for next PR)
ggml-ci
* kv-cache : some comments
ggml-ci
* context : fix graph reserve for multiple sequences
ggml-ci
* kv-cache : fix typo [no ci]
* kv-cache : fix find_slot() logic for free slots
ggml-ci
* llama : add TODO for deprecating the defrag API in the future
* kv-cache : improve find_slot() using min/max seq pos info
ggml-ci
* llama : handle aborts and compute errors
ggml-ci
* memory : extract state into llama_memory_state
ggml-ci
* kv-cache : add comments
ggml-ci
* server : update batching logic to reset n_batch on successful decode
* server : upon full re-processing, remove the sequence from the cache
* kv-cache : add TODO for doing split_equal when split_simple fails
ggml-ci
* add distilbert
* small fixes
* add note for LLM_ARCH_DISTIL_BERT
* Use MODEL_ARCH.BERT for DistilBert
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Co-authored-by: dinhhuy <huy.dinh@brains-tech.co.jp>
* convert: add support for BertForSequenceClassification
* add support for reranking using BertForSequenceClassification
* merge checks of eos and sep
* fix lint
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Co-authored-by: dinhhuy <huy.dinh@brains-tech.co.jp>
