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Description
Summary
Implement and finalize src/speculators/models/independent.py to support initial speculative decoding algorithms requiring an independent or separate draft model as the speculator.
References
- Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation
 - Fast Inference from Transformers via Speculative Decoding
 
Acceptance Criteria
Classes and Test Cases
- Implement 
IndependentSpeculatorConfigandIndependentSpeculatorfollowing the example insrc/speculators/models/eagle.py. - Ensure compatibility with 
SpeculatorModelConfig.from_pretrainedandSpeculatorModel.from_pretrained. - Implement full test cases following the examples in 
tests/unit/models/test_eagle_config.pyandtests/unit/models/test_eagle_model.py. 
IndependentSpeculatorConfig
- Include all relevant hyperparameters expected to change or be configured to construct a working Speculator model as defined in the referenced papers.
 
IndependentSpeculator
- Correctly create the required architecture from a given 
IndependentSpeculatorConfig. - Enable loading and saving of weights.
 - Integrate seamlessly with the existing system.
 
TokenProposal Functionality
- Implement any missing 
TokenProposalmethods or functionality as defined in the papers, or expand current implementations as needed. 
Out of Scope (Future Targets)
- Implement a functioning forward pass for 
SpeculatorModelcompatible with training flows. - Implement a functioning generate pass for 
SpeculatorModelcompatible with generation flows. - Create an Algorithm factory to handle preconfigured hyperparameters for the desired supported algorithms.
 
ruipeterpan
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enhancementNew feature or requestNew feature or requestgood first issueGood for newcomersGood for newcomers