ssz1111/Ctx2Skill-Skills
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updated a dataset about 5 hours ago
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ssz1111/Ctx2SkillOrganizations
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MENTOR: Efficient Multimodal-Conditioned Tuning for Autoregressive Vision Generation Models
Paper • 2507.09574 • Published
GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completion
Paper • 2502.11471 • Published • 2
BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation for Large Language Models via Lens of Dynamic Interactions
Paper • 2510.05318 • Published • 22
A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks
Paper • 2510.05608 • Published • 4
From Context to EDUs: Faithful and Structured Context Compression via Elementary Discourse Unit Decomposition
Paper • 2512.14244 • Published • 2
FaithLens: Detecting and Explaining Faithfulness Hallucination
Paper • 2512.20182 • Published • 9
InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
Paper • 2601.06666 • Published • 1
From Context to Skills: Can Language Models Learn from Context Skillfully?
Paper • 2604.27660 • Published • 161
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reacted to vicgalle's post with 🤝🤯 4 months ago
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Can you merge models of different sizes? ⚗️
Well, yes, if the models are somewhat compatible. Here is an experiment I did. I wanted to merge two of the best performing models: mlabonne/NeuralBeagle14-7B and jeonsworld/CarbonVillain-en-10.7B-v4
Here is my recipe:
1. Expand the layers of NeuralBeagle to 10.7B ala frankenmerge.
2. DPO-tune the previous model with a high-quality preference dataset, argilla/distilabel-intel-orca-dpo-pairs
3. Merge the previous model with CarbonVillain (needs —allow-crimes in mergekit! 🔪)
And here is the resulting model, CarbonBeagle-11B, which ranked top in the leaderboard for its size class:
vicgalle/CarbonBeagle-11B
Well, yes, if the models are somewhat compatible. Here is an experiment I did. I wanted to merge two of the best performing models: mlabonne/NeuralBeagle14-7B and jeonsworld/CarbonVillain-en-10.7B-v4
Here is my recipe:
1. Expand the layers of NeuralBeagle to 10.7B ala frankenmerge.
2. DPO-tune the previous model with a high-quality preference dataset, argilla/distilabel-intel-orca-dpo-pairs
3. Merge the previous model with CarbonVillain (needs —allow-crimes in mergekit! 🔪)
And here is the resulting model, CarbonBeagle-11B, which ranked top in the leaderboard for its size class:
vicgalle/CarbonBeagle-11B
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upvoted an article 4 months ago
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Merge Large Language Models with mergekit
mlabonne
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