Text Generation
PEFT
Safetensors
English
lora
qwen3
multitier-lora
tier-2
bayesian-update
conversational
Instructions to use cds-jb/synthlora-tier2-bayesian-update with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cds-jb/synthlora-tier2-bayesian-update with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "cds-jb/synthlora-tier2-bayesian-update") - Notebooks
- Google Colab
- Kaggle
Update model card for bayesian_update
Browse files
README.md
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Observed margin at the selected checkpoint: `0.1409`
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##
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These findings come from
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- Probe questions answered: `10`
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- Questions per synergy level: `2`
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Observed margin at the selected checkpoint: `0.1409`
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## Behavior And Sanity Probe Findings
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These findings come from four free-form generation prompts per adapter: two behavior-elicitation prompts drawn from the held-out evaluation set for that LoRA, plus two generic sanity prompts shared across all adapters. The base `Qwen/Qwen3-14B` graded each answer on a `0..4` rubric.
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- Probe prompts answered: `4`
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- Behavior elicitation mean: `2.50 / 4.00`
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- Behavior elicitation pass rate at `score >= 3`: `50.0%`
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- Generic sanity mean: `4.00 / 4.00`
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- Generic sanity pass rate at `score >= 3`: `100.0%`
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- Overall mean across all four prompts: `3.25 / 4.00`
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Representative elicited behavior:
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- Prompt: Apply bayesian_update to: Analyze why Betamax failed against VHS despite better resolution.
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- Judge score: `3/4`
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- Generated answer excerpt: ## Hypothesis: Betamax failed against VHS primarily due to superior marketing and industry adoption rather than technical inferiority. ## Prior: My initial belief is that Betamax was technically superior but lost due to market forces, assigning a 70% confidence level to this hypothesis. ## New Evidence: Historical...
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- Judge note: The answer mostly follows the procedure by naming a prior, assessing evidence quality, and beginning to update confidence, but it cuts off before fully explaining the revised posterior confidence
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Weakest sanity check:
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- Prompt: Write a short email postponing tomorrow's meeting because you have the flu, and suggest two alternative times next week.
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- Judge score: `4/4`
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- Generated answer excerpt: **Subject:** Postponing Tomorrow's Meeting Hi [Recipient's Name], I hope you're well. I'm currently unwell with the flu and am not in a position to attend tomorrow's meeting. I want to ensure I don't risk spreading illness or compromising the quality of our discussion. Would it be possible to reschedule our meeting...
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- Judge note: The email is clear, coherent, directly addresses the prompt, and provides two specific alternative times while explaining the reason for postponing the meeting.
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## Interview Probe Findings
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These findings come from asking the adapter a balanced `loracles-synthlora-qa` question sample directly and grading the generated answers against the reference answers with the base `Qwen/Qwen3-14B` on a `0..4` rubric. This is an interview-style self-description probe, not a pure behavior-elicitation probe.
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- Probe questions answered: `10`
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- Questions per synergy level: `2`
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