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🧠 FastFlowLM v0.9.6 β€” More Qwen3 Variants & Penalty Logic Fix

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@FastFlowLM FastFlowLM released this 28 Aug 20:16
· 1187 commits to main since this release
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FastFlowLM v0.9.6 introduces powerful new models and fine-tunes sampling behavior to match expected transformer behavior more accurately.


✨ What's New

πŸ†• 1. New Model Support

  • βœ… qwen3-tk:4b β€” Qwen3-4B Thinking model, supporting up to 256k context length (default 32768)
  • βœ… qwen3-it:4b β€” Qwen3-4B Instruction-tuned model (no think mode), supporting up to 256k context length (default 32768)
  • βœ… deepseek-r1-0528:8b β€” DeepSeek-R1 0528 distilled variant of Qwen3:8b, supporting up to 64k context length (default 16384)

These additions expand FastFlowLM's coverage of task-optimized and instruction-tuned models.


πŸ› οΈ 2. Penalty Handling Fixes

Behavior Update

  • Now, both repetition_penalty and frequency_penalty:
    • Do nothing when set to 1.0 (consistent with HuggingFace Transformers).
    • Apply penalty when > 1.0
    • Apply reward (encouragement) when < 1.0, not recommended.

Defaults Updated

  • The default values for both penalties are now set to:
    repetition_penalty = 1.1
    frequency_penalty = 1.1
    

This makes the decoding behavior clearer and more intuitive for advanced users.


βœ… Usage Reminder

Instruction-tuned Qwen3:

flm run qwen3-it:4b

Thinking-only Qwen3:

flm run qwen3-tk:4b

DeepSeek R1 0528:

flm run deepseek-r1-0528:8b

This release improves flexibility in model selection and ensures better alignment with standard decoding semantics.