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feat(transformers): upgrade modeling_utils/RoPE/optimization/cache_utils etc to v4.50
fix cache_utils
Add beam_search & Add ForCausalLMLoss
fix beam_search
* examples/codellama * test llama * update transformers version to 4.50 * update transformers version 4.51 * download checkpoints readme * correct load name * move files * revert pyproject
fix cache_utils bugs
Align v450
Revert "Align v450"
* feat(transformers): upgrade modeling_utils/RoPE/optimization/cache_utils etc to v4.50 * feat(transformers): upgrade modeling_utils/RoPE/optimization/cache_utils etc to v4.50 * feat(transformers): upgrade modeling_utils/RoPE/optimization/cache_utils etc to v4.50 * feat(transformers): upgrade modeling_utils/RoPE/optimization/cache_utils etc to v4.50 * precommit * fix cache_util * update generation_util, logit_processor, stopping_criteria, candidate_generator * fix cache_utils * Add beam_search&For ForCausalLMLoss loss * update modeling_outputs * update beam_search * pre-commit check * add support for dynamic input * add beam search py * fix tie_weight dtype mismatch in pynative mode for albert * fix beam_search * fix bug of dynamic input * add _supports_dynamic_input to PretrainedModel * fix pynative synchronize bug for albert[temporal] * support multimodal for init_static_cache[hack implementation] * fix cache_utils bugs * fix cumsum does not support int64 --------- Co-authored-by: Chaoran Wei <77485245+wcrzlh@users.noreply.github.com> Co-authored-by: Mark-ZhouWX <zhouwuxing000@gmail.com> Co-authored-by: liuchuting <liuchuting1@huawei.com>
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