Support for BharatGen's Param2MoE model architecture#43888
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bhargav-patel-29 wants to merge 10 commits intohuggingface:mainfrom
Open
Support for BharatGen's Param2MoE model architecture#43888bhargav-patel-29 wants to merge 10 commits intohuggingface:mainfrom
bhargav-patel-29 wants to merge 10 commits intohuggingface:mainfrom
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Hi @bhargav-patel-29, thank you for the PR! Before we review, can you convert the PR to |
…oe.py & added tests file
…as suggested in CI/CD pipeline checks
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[For maintainers] Suggested jobs to run (before merge) run-slow: auto, param2moe |
Contributor
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View the CircleCI Test Summary for this PR: https://huggingface.co/spaces/transformers-community/circle-ci-viz?pr=43888&sha=d46c70 |
This was referenced Apr 29, 2026
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What does this PR do?
This PR adds support for Param-2-17B-MoE-A2.4B, a large-scale Mixture-of-Experts (MoE) causal language model.
Param-2-17B-MoE-A2.4B uses a Hybrid Dense + MoE architecture with 17B total parameters while activating only 2.4B parameters per token, enabling high model capacity with efficient inference cost.
The model is pretrained from scratch with strong multilingual capabilities and particular emphasis on linguistic diversity and Indian language representation. It is released as a pretrained base model intended for downstream fine-tuning.
This PR introduces the following components:
configuration_param2moe.pyParam2MoEConfigmodeling_param2moe.pyParam2MoEModelParam2MoEForCausalLM__init__.pyAutoConfigAutoModelAutoModelForCausalLMThis integration enables seamless loading, inference, and downstream fine-tuning using standard Transformers APIs.
Fixes # (issue)
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Who can review?
Text models:
@ArthurZucker
@Cyrilvallez