commit fe2be2d06dafff810ebb16600af30aa316bba9e3 Author: ModelHub XC Date: Mon Sep 7 06:18:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: wallfacers/weft-lineage-extractor-3b Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..2d5702f --- /dev/null +++ b/README.md @@ -0,0 +1,148 @@ +--- +license: other +license_name: weft-research +license_link: https://github.com/wallfacers/data-weave +pipeline_tag: text-generation +library_name: transformers +base_model: Qwen/Qwen2.5-Coder-3B-Instruct +tags: +- data-lineage +- etl +- sql +- code +- lora +- research-artifact +language: +- en +datasets: +- wallfacers/weft-script-lineage-synth +--- + +# weft-lineage-extractor-3b + +The **efficient tier** of the Weft lineage-extractor family: a 3B code model (LoRA +fine-tuned, merged) that extracts **table- and column-level data lineage** from ETL scripts +as structured JSON. Deployable on a single 12 GB consumer GPU. Trained on real-world GitHub +ETL scripts with tri-vendor consensus silver labels. + +This repository ships **three branches** covering the table↔column trade-off frontier: + +| Branch | Variant | Table P / R / F1 | Column P / R / F1 | Positioning | +|---|---|---|---|---| +| **`main`** | loss-weighted W=3 (`run-tri-3b-lw3`) | 0.834 / 0.734 / **0.781** | 0.910 / 0.755 / **0.825** | Best balanced 3B single model | +| `tri-column-specialist` | plain full-column (`run-tri-3b`) | 0.822 / 0.645 / 0.723 | 0.914 / 0.949 / **0.931** | Best column F1 | +| `tri-table-specialist` | 31% column density (`run-tri-3b-col50`) | 0.825 / **0.776** / 0.800 | 0.912 / 0.423 / 0.578 | Best table recall | + +*Benchmark: 129 non-empty real GitHub scripts, tri-vendor consensus gold, greedy decoding at +1024 max new tokens. Column metrics are conditional on matched tables.* + +**Which branch?** One model for both tables and columns → `main`. Maximum column quality +(pair it with a table specialist via inference-time fusion) → `tri-column-specialist`. +Maximum table recall → `tri-table-specialist`. + +## Method highlight: table-token loss weighting + +The 3B table↔column frontier is driven by **gradient imbalance, not just capacity**: in the +answer JSON, high-entropy column tokens outnumber table tokens **4.39 : 1**, drowning the +table-name gradient. Re-weighting the loss on table-structure tokens (W=3) lifts table recall +0.645 → **0.734** with no data removal and no extra capacity, at table-precision parity +(0.834, McNemar n.s.). Loss weighting **strictly dominates column-density dilution**: at +equal table recall it keeps ~**+0.15 column F1** that dilution would destroy. + +## Label credibility (tri-vendor consensus) + +Gold and silver labels are **2-of-3 consensus across three independent vendors** +(qwen-max ∩ deepseek-v4-pro ∩ GPT-5.6). GPT-5.6, which never participated in constructing +the earlier two-vendor labels, independently agrees with them at **0.976 (table) / 0.958 +(column)**; models trained only on the two-vendor subset reach 0.782 table recall on edges +only GPT-5.6 confirms — evidence the model learns real lineage, not one vendor's labeling +habits. Total teacher-labeling cost: **$2.42**. + +## Honest boundaries + +- **Reduced, not eliminated, circularity**: labels remain LLM-consensus silver; no human gold. +- **Governance routing**: 3-of-3 vendor-unanimous cases (~70%) are candidates for an + auto-adopt layer; vendor-disagreement cases (~30%) route to human review. The model narrows + the review queue; it does not eliminate review. +- **Convention A exclusions** (dynamically-built table names, commented-out/printed SQL, temp + views) are deliberate scope boundaries of static extraction, not bugs. +- **The strict dual gate (table R ≥ 0.75 and column F1 ≥ 0.85) is unreachable at 3B** — shown + twice independently (loss-weight sweep; r=64 capacity stack). It remains unreachable by any + *single* model even at 14B; the quality path is + [weft-lineage-extractor-14b](https://huggingface.co/wallfacers/weft-lineage-extractor-14b) + (best balanced 0.799 / 0.856) plus inference-time dual-expert fusion. + +## Training details + +| | | +|---|---| +| Base model | [Qwen/Qwen2.5-Coder-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct) | +| Method | LoRA r=32, α=64, bf16 (merged into this checkpoint) | +| Data | 1,154 real GitHub ETL scripts, tri-vendor consensus silver labels (tables + columns) | +| Branch deltas | `main`: answer table-token loss ×3 · `tri-table-specialist`: 31% column density · `tri-column-specialist`: full columns | +| Schedule | 3 epochs, effective batch 16, lr 2e-4 cosine, max seq 2048 | + +## Usage + +### vLLM (recommended for batch extraction — continuous batching, OpenAI-compatible) + +```bash +pip install vllm +vllm serve wallfacers/weft-lineage-extractor-3b --revision main \ + --dtype bfloat16 --max-model-len 2048 --gpu-memory-utilization 0.9 --port 8000 +``` + +```python +from vllm import LLM, SamplingParams +llm = LLM(model="wallfacers/weft-lineage-extractor-3b", revision="main", + dtype="bfloat16", max_model_len=2048) +sp = SamplingParams(temperature=0.0, max_tokens=256) # deterministic decoding +outs = llm.chat([[{"role": "system", "content": SYSTEM_PROMPT}, + {"role": "user", "content": "task_type: PYTHON\nscript:\n" + script}]], sp) +print(outs[0].outputs[0].text) +``` + +### transformers (single request / interactive, p50 ≈ 360 ms) + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +REPO, REV = "wallfacers/weft-lineage-extractor-3b", "main" +tok = AutoTokenizer.from_pretrained(REPO, revision=REV) +model = AutoModelForCausalLM.from_pretrained(REPO, revision=REV, + dtype="bfloat16", device_map="cuda") +``` + +System prompt (shared across the family): + +```text +You are a data lineage extractor for ETL scripts. Given a PYTHON, SHELL, SCALA or JAVA task +script (Spark/Flink jobs included), output ONLY a JSON object {"reads": [...], "writes": [...]} +where each item is {"table": str, "columns": [str] or null}. Rules: include a table only if +its literal name appears in the script text; ignore dynamically-built table names, +commented-out SQL, and SQL that is merely printed or logged; if nothing is read or written, +output {"reads": [], "writes": []}. +``` + +**Output schema**: `{"reads": [{"table": str, "columns": [str] | null}], "writes": [...]}`. + +**Cost note**: lineage answers are short (~22 output tokens/request, prefill-bound). Self-hosted +on a single consumer GPU the marginal cost approaches electricity (≈$0.004 / 1k requests) — +1–2 orders of magnitude below cloud LLM APIs for high-volume batch extraction. Full +throughput/cost ledger: `out/cost-analysis-068.md` in the GitHub repo. + +## Model family + +| Model | Role | +|---|---| +| [weft-lineage-extractor-14b](https://huggingface.co/wallfacers/weft-lineage-extractor-14b) | best single models (3 branches) | +| [weft-lineage-extractor-7b](https://huggingface.co/wallfacers/weft-lineage-extractor-7b) | scale-curve point (capacity-valley negative result) | +| [weft-lineage-extractor-3b](https://huggingface.co/wallfacers/weft-lineage-extractor-3b) | **this repo — efficient tier, 3 branches** | +| [weft-lineage-extractor-1.5b](https://huggingface.co/wallfacers/weft-lineage-extractor-1.5b) | synthetic-only negative-result artifact | +| [weft-lineage-extractor-0.5b](https://huggingface.co/wallfacers/weft-lineage-extractor-0.5b) | scale-curve point (synthetic-only) | +| [weft-lineage-extractor-jvm-1.5b](https://huggingface.co/wallfacers/weft-lineage-extractor-jvm-1.5b) | cross-language (Scala/Java) negative result | +| [weft-script-lineage-synth](https://huggingface.co/datasets/wallfacers/weft-script-lineage-synth) | synthetic corpus + evidence reports | + +Full evidence ledger (4.39:1 token measurement, frontier-dominance +0.15, McNemar parity, +dual-gate negative results): +[github.com/wallfacers/data-weave](https://github.com/wallfacers/data-weave) +(`ml/lineage-extractor/out/PAPER-EVIDENCE-068.md`). diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..bdf7919 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,54 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0]['role'] == 'system' %} + {{- messages[0]['content'] }} + {%- else %} + {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }} + {%- endif %} + {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0]['role'] == 'system' %} + {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} + {%- else %} + {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- for message in messages %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %} + {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {{- '<|im_start|>' + message.role }} + {%- if message.content %} + {{- '\n' + message.content }} + {%- endif %} + {%- for tool_call in message.tool_calls %} + {%- if tool_call.function is defined %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {{- tool_call.arguments | tojson }} + {{- '}\n' }} + {%- endfor %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- message.content }} + {{- '\n' }} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} + {{- '<|im_end|>\n' }} + {%- endif %} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- '<|im_start|>assistant\n' }} +{%- endif %} diff --git a/config.json b/config.json new file mode 100644 index 0000000..cd9c2f3 --- /dev/null +++ b/config.json @@ -0,0 +1,69 @@ +{ + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "hidden_act": "silu", + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": 11008, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 32768, + "max_window_layers": 36, + "model_type": "qwen2", + "num_attention_heads": 16, + "num_hidden_layers": 36, + "num_key_value_heads": 2, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000.0, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": true, + "transformers_version": "5.5.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 151936 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..79e284a --- /dev/null +++ b/generation_config.json @@ -0,0 +1,13 @@ +{ + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "repetition_penalty": 1.05, + "temperature": 0.7, + "top_k": 20, + "top_p": 0.8, + "transformers_version": "5.5.0" +} diff --git a/model.safetensors b/model.safetensors new file mode 100644 index 0000000..578d0f0 --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bfcebc41ba3518749ca9638e9e0b524f757bd5f8ea650b5df8c22b51e96a5716 +size 6171927112 diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..34510ff --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8 +size 11421892 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..e4fb8c3 --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,29 @@ +{ + "add_prefix_space": false, + "backend": "tokenizers", + "bos_token": null, + "clean_up_tokenization_spaces": false, + "eos_token": "<|im_end|>", + "errors": "replace", + "extra_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|object_ref_start|>", + "<|object_ref_end|>", + "<|box_start|>", + "<|box_end|>", + "<|quad_start|>", + "<|quad_end|>", + "<|vision_start|>", + "<|vision_end|>", + "<|vision_pad|>", + "<|image_pad|>", + "<|video_pad|>" + ], + "is_local": false, + "model_max_length": 32768, + "pad_token": "<|endoftext|>", + "split_special_tokens": false, + "tokenizer_class": "Qwen2Tokenizer", + "unk_token": null +}