Release btl-2-coder-7B api4k-template1k LoRA adapter

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* 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

README.md

@@ -0,0 +1,98 @@
+---
+license: apache-2.0
+base_model: unsloth/Qwen2.5-Coder-7B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+  - code
+  - code-review
+  - security
+  - qwen2.5-coder
+  - lora
+  - bad-theory-labs
+model_name: btl-2-coder-7B
+---
+
+# BTL-2 Coder 7B
+
+BTL-2 Coder 7B is a LoRA adapter for `unsloth/Qwen2.5-Coder-7B-Instruct`, trained for structured code-review findings.
+
+## Intended Use
+
+Use this model for local-first code review:
+
+- SQL injection
+- path traversal
+- authorization bypass
+- missing error handling
+- boundary/off-by-one logic
+- related security and correctness bugs
+
+It is not yet a general autonomous coding agent and should not be marketed as a SWE-Bench repair model.
+
+## Training
+
+- Base: `unsloth/Qwen2.5-Coder-7B-Instruct`
+- Trainer: Unsloth LoRA SFT
+- Data: `4,000` API teacher traces + `1,000` template traces
+- Split: `4,500` train / `500` eval
+- Epochs: `2`
+- Max length: `4096`
+
+Only redacted, opt-in traces should be used for future training.
+
+## Prompt
+
+Use strict schema prompting:
+
+```text
+Return only a JSON array. No markdown and no wrapper object.
+Each finding must include: severity, file, line, title, evidence, recommendation, confidence.
+severity must be exactly one of: critical, high, medium, low.
+Never put a category in severity.
+confidence must be a number from 0 to 1, never a string label.
+Every finding must include concrete evidence and a non-empty recommendation.
+```
+
+Example output:
+
+```json
+[
+  {
+    "severity": "critical",
+    "file": "src/users.ts",
+    "line": 42,
+    "title": "SQL injection through string-built query",
+    "evidence": "The user id is concatenated directly into the SQL string.",
+    "recommendation": "Use a parameterized query.",
+    "confidence": 0.96
+  }
+]
+```
+
+## Evaluation
+
+| Eval | JSON parse | Schema valid | Numeric confidence | Category hit | File hit | Precision | Recall | Weighted severity recall |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| Heldout 100 strict | 1.000 | 0.952 | 1.000 | 0.783 | 0.840 | - | - | - |
+| Heldout 30 strict v2 | 1.000 | 0.975 | 1.000 | 0.867 | 0.867 | - | - | - |
+| Seeded 15 strict | 1.000 | 1.000 | 1.000 | 0.933 | 1.000 | 0.933 | 0.933 | 0.956 |
+
+## Limitations
+
+- Strict schema prompting is required for best results.
+- The model may miss subtle multi-file issues.
+- The model can produce plausible but incorrect findings; keep human review in the loop.
+- Do not use on private repositories unless you control the inference environment and data policy.
+
+## Release Artifacts
+
+This Hugging Face repo should include:
+
+- `adapter_model.safetensors`
+- `adapter_config.json`
+- `tokenizer.json`
+- `tokenizer_config.json`
+- `chat_template.jinja`
+- `training_args.bin`
+- this `README.md`

SHA256SUMS

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+74cf19bc8a8e21d384d24026ae06fcba2b0168826ae847d46dff2107cecd0e20  SHA256SUMS
+755d5b561d039e97ad67b99c75dd1f8312d768f7f1879a120e2fcef33596e274  adapter_config.json
+8436e2f27afe3726af40373e26bfcb2c764513ff2737067e33d3002c07098ade  adapter_model.safetensors
+cd8e9439f0570856fd70470bf8889ebd8b5d1107207f67a5efb46e342330527f  chat_template.jinja
+ea43b288542655d72d632195ab9b58ca2cd9532c292bf6667827ce899ad196bc  tokenizer.json
+7cd38d182a09f57796af5ef7dbe15c9fa8595fdaa94c5cba9a3065f6e987b1fd  tokenizer_config.json
+5811e0147d545faafa9083e10f21552c17b4e3ae375a37b3c8acd79751833548  training_args.bin

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen2ForCausalLM",
+    "parent_library": "transformers.models.qwen2.modeling_qwen2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/qwen2.5-coder-7b-instruct-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "q_proj",
+    "o_proj",
+    "down_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+oid sha256:8436e2f27afe3726af40373e26bfcb2c764513ff2737067e33d3002c07098ade
+size 645975704

chat_template.jinja

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+{%- 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 <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|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<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- 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 %}

tokenizer.json

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tokenizer_config.json

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+  "errors": "replace",
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+  "is_local": false,
+  "model_max_length": 32768,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
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+  }
+}

training_args.bin

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