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README.md
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---
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base_model: mlx-community/Qwen3.6-35B-A3B-4bit
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library_name: mlx
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pipeline_tag: text-generation
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tags:
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- lora
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- mlx
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- effect-ts
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- typescript
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- code-generation
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license: apache-2.0
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---
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# effect-qwen36-35b-write-lora — Effect v4 TypeScript champion LoRA (`v7s43_i200`)
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Rank-8 LoRA adapter on **`mlx-community/Qwen3.6-35B-A3B-4bit`** that writes idiomatic
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**Effect v4** (`effect@4.0.0-beta.8x`) TypeScript: `Context.Service`/`Layer` services,
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`Effect.gen` pipelines, `Schema`, `Data.TaggedError`, and typed-error seams — verified by a
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best-of-N + TypeScript-compiler product harness, not by eyeballing.
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## Result — the served PRODUCT (not raw greedy)
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- **best-of-16 + tsc gate: 23/24** on a frozen held-out set. This is the deliverable metric.
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- Judged on the served product pipeline (sample N → import-resolver → `tsc --strict`), **never
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raw single-greedy**: raw greedy is ceiling-blocked at ~9.67/24; the compiler verifier is what
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lifts it to 23/24. (A perfect 0/1 verifier means a returned "compiles" is genuinely verified.)
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## Adapter
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- LoRA: rank 8, scale 20, dropout 0, 16 layers; lr 1e-5; warm-started from a continued-pretrain
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adapter. Apply **unfused** on top of the 4-bit base.
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- `adapters.safetensors` = 1,025,848,752 bytes (the byte-intact champion).
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## Use (MLX)
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```bash
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python -m mlx_lm generate \
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--model mlx-community/Qwen3.6-35B-A3B-4bit \
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--adapter-path . \
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--prompt "Write an Effect service that fetches a user by id over HTTP, with a typed NotFound error."
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```
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For the actual deliverable, serve it behind a best-of-N + `tsc` gate (the raw adapter alone is not
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the product). The same champion also serves a surgical **EDIT** lane (best-of-N SEARCH/REPLACE →
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apply → `tsc` gate), tsc-verified.
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## Related
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- Fused full model: `jrad123777/effect-qwen36-35b-mlx` · GGUF: `jrad123777/effect-qwen36-35b-gguf`
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- Companion React+seam LoRA: `jrad123777/effect-qwen36-35b-react-lora`
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