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Achievements

Achievement: Pair Extraordinairex3Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx3Achievement: Arctic Code Vault Contributor

Achievements

Achievement: Pair Extraordinairex3Achievement: YOLOAchievement: QuickdrawAchievement: Pull Sharkx3Achievement: Arctic Code Vault Contributor

Organizations

@IBM @fossasia @ansible-community @nit-andhra-pradesh @konveyor @c2siorg @instructlab

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kmehant/README.md

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  1. konveyor/move2kube Public

    Move2Kube is a command-line tool for automating creation of Infrastructure as code (IaC) artifacts. It has inbuilt support for creating IaC artifacts for replatforming to Kubernetes/Openshift.

    Go 397 121

  2. ansible-community/ansible-bender Public

    ansible-playbook + buildah = a sweet container image

    Python 691 75

  3. konveyor/move2kube-transformers Public

    Repository for storing Move2Kube custom transformers

    WebAssembly 6 11

  4. konveyor/move2kube-api Public

    HTTP REST API for move2kube

    Go 6 18

  5. huggingface/transformers Public

    🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

    Python 146k 29.3k

  6. huggingface/peft Public

    🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

    Python 18.8k 1.9k

244 contributions in the last year

Contribution Graph
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Activity overview

Contributed to foundation-model-stack/fms-hf-tuning, huggingface/transformers, foundation-model-stack/fms-acceleration and 24 other repositories
Loading A graph representing kmehant's contributions from June 09, 2024 to June 12, 2025. The contributions are 36% code review, 33% commits, 19% pull requests, 12% issues.

Contribution activity

June 2025

Created 11 commits in 3 repositories
Created 1 repository

Created a pull request in foundation-model-stack/fms-hf-tuning that received 7 comments

fix: saving logic for alora

Irrespective of the save_strategy, we only save once at the end of the training as per @kgreenewald. However, in such case we dont need save_model_…

+6 −38 lines changed • 7 comments
Opened 2 other pull requests in 1 repository
IBM/activated-lora 2 merged
Reviewed 3 pull requests in 2 repositories

Created an issue in IBM/activated-lora that received 2 comments

Adapter precision is not consistent with base model preicison

Adapter weights are always in full precision irrespective of the base model precision. This would be an issue with FSDP v1 where params should have…

2 comments
Opened 2 other issues in 1 repository
IBM/activated-lora 2 closed
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