transformers
d8590b4b - Add Doge model (#35891)

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208 days ago
Add Doge model (#35891) * Add Doge Model * Fix code quality * Rollback an error commit * Fix config for open-source weights * Revert "Fix config for open-source weights" This reverts commit 229cdcac10a6a4274d1dd13b729bc14c98eb0c76. * Add modular_doge * Update Doge inherits from Llama * Fix import bug * [docs] Add usage of doge model * Fix Doge import pretrainedconfig from modeling_utils to configuration_utils * [docs] remove trust remote code from doge * Fix dynamo bug in doge model * Update docstrings * Import apply_rotary_pos_emb and repeat_kv from Llama * Fix all nits * Fix code quality * Fix some bugs * Fix code quality * Remove inherited `_update_causal_mask` from Llama This leads to incorrect weight initialization. * Fix the wrong tensor orderings in DogeCDMoE * Fix attention mask bug We have to provide attention_mask for dynamic mask computation * Modify most implementations to inherit from Llama But there are two problems: 1. `flex_attention_forward` is not updated properly 2. `Example` error in the forward method of DogeForCausalLM * Modify CDMoE for batch efficient implementation * Uniform MoE configuration names, just like QwenMoE * Fix code quality * Fix code quality * Fix code quality * Add tp plan of CDMoE Module * Hybird DMA with sliding window * Update valid tokens greater than window size * Fix code quality * Add `convert_doge_weights_to_hf` * Fix STATE_DICT_MAPPING in convert_doge_weights_to_hf.py * Fix nits in modular_doge * Fix code quality * Fix all nits * Fix all nits * Make sure the attention function is updated inside the class * Fix code quality issues in the Doge model and add a test for it * Fix `test_generate` * Fix code quality * Fix nits fllowing suggestions * Fix code quality * Fix code quality issues * Fix nits * Fix code quality nits * Fix the missing parameters in the configuration. * Fix the missing parameters in the configuration. * Fix nits * Add initialization of attention * Fix last nits * Simplify dynamic mask generation logic * Rename router_logits to gate_logits for matching latest changes of MixtralModel * Rename typings for matching latest changes of MixtralModel * Fixes typo in comment * Update src/transformers/models/doge/modular_doge.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Fix code quality issues to match other modular * Fix code quality issues to match other modular * Fix the static compilation errors * Update model weights link * Fix code quality issues to match other modular * reapply modular and support for new outputs * style * simplify a lot * fix import location * reapply modular * fix * fix integration test --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co> Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
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