From dec1a19935b09349a73085745b7938132cd7b3b8 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Wed, 15 Jul 2026 14:53:09 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Kuyash/teptez-ai Source: Original Platform --- .gitattributes | 37 +++ Modelfile | 54 ++++ README.md | 335 +++++++++++++++++++++++++ chat_template.jinja | 54 ++++ config.json | 62 +++++ generation_config.json | 15 ++ model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 346 ++++++++++++++++++++++++++ qwen2.5-coder-7b-instruct.Q4_K_M.gguf | 3 + tokenizer.json | 3 + tokenizer_config.json | 203 +++++++++++++++ 14 files changed, 1124 insertions(+) create mode 100644 .gitattributes create mode 100644 Modelfile create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 qwen2.5-coder-7b-instruct.Q4_K_M.gguf create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..e5b3add --- /dev/null +++ b/.gitattributes @@ -0,0 +1,37 @@ +*.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 +qwen2.5-coder-7b-instruct.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/Modelfile b/Modelfile new file mode 100644 index 0000000..c919a17 --- /dev/null +++ b/Modelfile @@ -0,0 +1,54 @@ + +FROM qwen2.5-coder-7b-instruct.Q4_K_M.gguf +TEMPLATE """{{- if .Suffix }}<|fim_prefix|>{{ .Prompt }}<|fim_suffix|>{{ .Suffix }}<|fim_middle|> +{{- else if .Messages }} +{{- if or .System .Tools }}<|im_start|>system +{{- if .System }} +{{ .System }} +{{- end }} +{{- if .Tools }} + +# Tools + +You may call one or more functions to assist with the user query. + +You are provided with function signatures within : + +{{- range .Tools }} +{"type": "function", "function": {{ .Function }}} +{{- end }} + + +For each function call, return a json object with function name and arguments within with NO other text. Do not include any backticks or ```json. + +{"name": , "arguments": } + +{{- end }}<|im_end|> +{{ end }} +{{- range $i, $_ := .Messages }} +{{- $last := eq (len (slice $.Messages $i)) 1 -}} +{{- if eq .Role "user" }}<|im_start|>user +{{ .Content }}<|im_end|> +{{ else if eq .Role "assistant" }}<|im_start|>assistant +{{ if .Content }}{{ .Content }} +{{- else if .ToolCalls }} +{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}} +{{ end }} +{{- end }}{{ if not $last }}<|im_end|> +{{ end }} +{{- else if eq .Role "tool" }}<|im_start|>user + +{{ .Content }} +<|im_end|> +{{ end }} +{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant +{{ end }} +{{- end }} +{{- else }} +{{- if .System }}<|im_start|>system +{{ .System }}<|im_end|> +{{ end }}{{ if .Prompt }}<|im_start|>user +{{ .Prompt }}<|im_end|> +{{ end }}<|im_start|>assistant +{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}""" +SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful assistant.""" \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..09604e9 --- /dev/null +++ b/README.md @@ -0,0 +1,335 @@ +--- +language: en +license: apache-2.0 +base_model: Qwen/Qwen2.5-Coder-7B-Instruct +tags: + - security + - sast + - code-analysis + - vulnerability-detection + - triage + - gguf +pipeline_tag: text-generation +--- + +# teptez-ai + +**SAST finding triage model** — fine-tuned on real production security scan data to classify Static Application Security Testing findings as true positives, false positives, or uncertain, with CWE labels, confidence scores, and remediation guidance. + +--- + +## Overview + +Rule-based SAST tools generate enormous volumes of findings, a significant portion of which are false positives. Security analysts spend hours triaging noise instead of fixing real vulnerabilities. teptez-ai is a 7B-parameter LLM fine-tuned specifically to automate this triage step. + +Given a SAST finding (title, CWE, severity, code snippet, taint flow), teptez-ai returns a structured JSON verdict: + +- **true_positive** — finding is real, exploit path exists +- **false_positive** — finding is noise, safe to suppress +- **uncertain** — insufficient context, escalate to analyst + +Fine-tuned on production findings from the [Teptez](https://teptez.io) security platform — real codebases, real scan data, real analyst labels. + +### Key specs + +| Property | Value | +|---|---| +| Base model | Qwen2.5-Coder-7B-Instruct | +| Quantization | GGUF Q4_K_M | +| Model size | ~4.7 GB | +| Inference speed | ~100 tok/s (RTX 3090 24GB) | +| Context window | 8192 tokens | +| License | Apache 2.0 | + +--- + +## Benchmark Results + +Evaluated against **OWASP Benchmark v1.2** — the standard industry benchmark for SAST tools — using the official **Youden's J statistic** (`J = TPR − FPR`). + +> J = 0.0 is random. J = 1.0 is perfect. Open-source SAST tools typically score 0.30–0.45. + +### Head-to-head vs base model + +| Model | TPR | FPR | Youden J | vs base | +|---|---|---|---|---| +| **teptez-ai (Q4_K_M)** | **0.68** | **0.57** | **0.109** | **+0.048 (+79%)** | +| qwen2.5-coder-7b (base) | 0.66 | 0.60 | 0.061 | — | + +Fine-tuning delivers a **79% relative improvement** in Youden's J over the base model, primarily by cutting the false positive rate from 0.60 to 0.57 across the full benchmark. + +### Per-category breakdown + +| CWE Category | teptez-ai J | base J | Delta | +|---|---|---|---| +| Command Injection (CWE-78) | **0.40** | 0.22 | +0.18 | +| SQL Injection (CWE-89) | **0.33** | 0.18 | +0.15 | +| XSS (CWE-79) | **0.28** | 0.12 | +0.16 | +| Path Traversal (CWE-22) | **0.22** | 0.09 | +0.13 | +| Weak Randomness (CWE-330) | **0.13** | 0.05 | +0.08 | +| Crypto/Hash (CWE-327/328) | 0.00 | 0.01 | -0.01 | +| Auth/Authz (CWE-862/639) | 0.02 | 0.01 | +0.01 | +| Timing (CWE-208) | 0.05 | 0.04 | +0.01 | +| **Secure Cookie (CWE-614)** | **-0.08** | **0.52** | **-0.60 ⚠️** | + +**Strong on injection classes.** teptez-ai significantly outperforms the base model across all injection-type CWEs (cmdi/sqli/xss/path/weakrand). These are the highest-volume SAST categories in real codebases. + +**Securecookie regression.** CWE-614 (missing HttpOnly/Secure flags) shows a severe regression vs the base model. **Do not use teptez-ai to triage cookie security findings.** This is a known training artifact being fixed in the next round. + +**Dead categories.** Crypto, authz, and timing categories have near-zero Youden J on both models — 7B parameters are insufficient for these without full class context. Escalate to frontier models or human analysts. + +### Production run + +On **369 real production SAST findings** from live codebases: +- **17% rejected as false positive** (~63 findings suppressed) +- Injection-class findings: majority of suppressions, generally accurate +- Authz/crypto findings: some wrong suppressions (do not enable for these categories) + +--- + +## Usage + +### Recommended architecture + +Use teptez-ai as a **gated FP suppressor**, not a confirmer: + +``` +Rule-engine finding + │ + ▼ +Is CWE in injection classes? ──No──▶ Keep finding (don't run model) + │ Yes + ▼ +Run teptez-ai with full function + taint context + │ + ├── verdict: false_positive, confidence > 0.75 ──▶ Suppress finding + ├── verdict: true_positive ──▶ Keep finding + └── verdict: uncertain / confidence < 0.75 ──▶ Escalate to frontier model / analyst +``` + +**Only suppress on `false_positive`** — never on `true_positive`. The model is biased toward flagging (FPR 0.57), so a `false_positive` verdict is rare and higher-precision. + +**Injection-class CWEs only** (where Youden J ≥ 0.13): +- CWE-78 Command Injection +- CWE-79 Cross-Site Scripting +- CWE-89 SQL Injection +- CWE-22 Path Traversal +- CWE-330 Weak Randomness + +**Never auto-suppress**: +- CWE-614 Secure Cookie (regression — model worse than random) +- CWE-327/328 Weak Crypto/Hash (near-zero J) +- CWE-862/639 Auth/Authz/IDOR (near-zero J) +- CWE-208 Timing Attacks (near-zero J) + +### Running with llama.cpp / Ollama + +```bash +# Pull via Ollama +ollama pull hf.co/Kuyash/teptez-ai:Q4_K_M + +# Or run directly with llama.cpp +./llama-cli -m teptez-ai-Q4_K_M.gguf \ + --temp 0.1 \ + --top-p 0.9 \ + -n 512 \ + -p "" +``` + +### Python integration + +```python +import json +import requests + +def triage_finding(finding: dict) -> dict: + prompt = f"""<|im_start|>system +You are a SAST triage expert. Analyze this finding and return JSON with keys: +verdict (true_positive|false_positive|uncertain), confidence (0.0-1.0), +cwe (string), explanation (string), remediation (string). +<|im_end|> +<|im_start|>user +Finding: {finding['title']} +CWE: {finding.get('cwe_id', 'unknown')} +Severity: {finding.get('severity', 'MEDIUM')} +Code: +{finding.get('code_snippet', '')} + +Taint flow: {finding.get('data_flow', 'not available')} +<|im_end|> +<|im_start|>assistant +""" + response = requests.post("http://localhost:11434/api/generate", json={ + "model": "teptez-ai", + "prompt": prompt, + "stream": False, + "options": {"temperature": 0.1} + }) + text = response.json()["response"].strip() + # Strip markdown fences if present + if text.startswith("```"): + text = text.split("```")[1] + if text.startswith("json"): + text = text[4:] + return json.loads(text) + +# Gate: only run on injection CWEs +INJECTION_CWES = {"CWE-78", "CWE-79", "CWE-89", "CWE-22", "CWE-330"} + +def should_suppress(finding: dict) -> bool: + cwe = finding.get("cwe_id", "") + if cwe not in INJECTION_CWES: + return False # don't touch non-injection + result = triage_finding(finding) + return ( + result.get("verdict") == "false_positive" + and result.get("confidence", 0) >= 0.75 + ) +``` + +--- + +## Input / Output Format + +### Prompt template + +``` +<|im_start|>system +You are a SAST triage expert. Analyze this finding and return JSON. +<|im_end|> +<|im_start|>user +Finding: {title} +CWE: {cwe_id} +Severity: {severity} +Code: +{code_snippet} + +Taint flow: {data_flow} +<|im_end|> +<|im_start|>assistant +``` + +**Tips for best results:** +- Provide the **full function**, not just the flagged line — avoids "insufficient context" errors +- Include taint flow when available (source → sink path from your SAST tool) +- Keep code under 2048 tokens; truncate from the bottom if needed + +### Output schema + +```json +{ + "verdict": "true_positive" | "false_positive" | "uncertain", + "confidence": 0.85, + "cwe": "CWE-89", + "explanation": "User input from request.getParameter() flows directly into a string-concatenated SQL query with no parameterization or escaping.", + "remediation": "Replace string concatenation with a PreparedStatement: `conn.prepareStatement(\"SELECT * FROM users WHERE id = ?\")` and bind the parameter with `stmt.setString(1, userId)`." +} +``` + +| Field | Type | Description | +|---|---|---| +| `verdict` | string | `true_positive`, `false_positive`, or `uncertain` | +| `confidence` | float | 0.0–1.0; scores < 0.75 should be treated as uncertain | +| `cwe` | string | Classified CWE identifier | +| `explanation` | string | Why the model reached this verdict | +| `remediation` | string | Concrete fix recommendation | + +--- + +## Limitations + +### Known issues (as of current release) + +**CWE-614 Secure Cookie — severe regression.** +teptez-ai scores Youden J = −0.08 on secure cookie findings, compared to 0.52 for the base model. This is a catastrophic regression caused by training data imbalance. Do not use teptez-ai for HttpOnly/Secure flag findings until this is fixed. + +**High overall FPR (0.57).** +The model over-flags — it sees vulnerability in safe code, especially in crypto, auth, and cookie-related code patterns. A `false_positive` verdict is more reliable than a `true_positive` verdict because it swims against the model's bias. + +**Dead categories (crypto/authz/timing).** +CWE-327/328/614/862/639/208 have near-zero Youden J. The model lacks sufficient training signal for these categories. Use a frontier model (Claude, GPT-4o, Gemini) or a human analyst for these. + +**7B parameter ceiling.** +Subtle IDOR, broken access control, and privilege escalation patterns require understanding class hierarchy, authentication flow, and business logic across multiple files. A 7B model with single-function context cannot reliably detect these. + +**GGUF Q4_K_M quantization.** +~4-bit quantization introduces slight accuracy loss vs fp16. For maximum accuracy, use the Q8_0 variant (if available) or the full fp16 model. + +**Snippet-only inputs fail.** +If you pass only the flagged 1–3 lines without the surrounding function, the model frequently returns `uncertain` with "insufficient context." Always include the full function body. + +--- + +## Reproducing the Benchmark + +```bash +# 1. Clone OWASP Benchmark +git clone https://github.com/OWASP-Benchmark/BenchmarkJava +cd BenchmarkJava && mvn package -DskipTests + +# 2. Run evaluation (requires teptez-ai running on Ollama) +python salad/eval/owasp_eval.py # stratified sample → results.jsonl +python salad/eval/owasp_score.py # Youden J + per-category table +python salad/eval/owasp_compare.py # head-to-head vs base model +``` + +The eval script uses a stratified sample of OWASP BenchmarkJava test cases, covering all CWE categories proportionally. Scoring follows the official OWASP methodology (Youden's J = TPR − FPR). + +--- + +## Roadmap + +The following improvements are planned for the next fine-tuning round: + +### Round 2 targets + +| Improvement | Target metric | +|---|---| +| Flood training with safe-code negatives (50/50 balance) | FPR < 0.30 | +| Fix securecookie regression (restore CWE-614 training data) | J(CWE-614) > 0.40 | +| Add dead-category examples (crypto/authz/timing) | J(CWE-327/328) > 0.10 | +| Calibrate confidence score (train explicit `uncertain` label) | Confidence Brier score < 0.15 | +| Full-function context at train AND inference | Reduce "uncertain" on short snippets | + +**Root cause of FPR problem:** Current training set is vuln-heavy (more vulnerable examples than safe ones). The model learned to flag aggressively. Rebalancing to 50/50 with explicit safe variants (parameterized SQL, escaped HTML, validated paths, compare_digest timing-safe comparisons, role-checked endpoints, strong ciphers) is the single highest-leverage fix. + +**Securecookie fix:** Restore the original training examples for CWE-614 that were accidentally dropped. Mix with new negative examples. Lower learning rate for this category to avoid forgetting again. + +**No catastrophic forgetting:** Round 2 will mix old injection data with new negatives and use a lower learning rate on the balanced set, following standard continual learning practice. + +### Round 3 vision + +- Full-function + cross-file taint context (requires longer context fine-tune) +- Multi-label output (multiple CWEs per finding) +- Confidence calibration verified against held-out production labels +- Youden J > 0.25 across all injection categories +- FPR < 0.30 overall + +--- + +## Citation + +If you use teptez-ai in your research or tooling, please cite: + +```bibtex +@misc{teptez-ai-2026, + title = {teptez-ai: A Fine-Tuned LLM for SAST Finding Triage}, + author = {Teptez Security}, + year = {2026}, + publisher = {HuggingFace}, + url = {https://huggingface.co/Kuyash/teptez-ai} +} +``` + +Evaluated against [OWASP Benchmark v1.2](https://owasp.org/www-project-benchmark/) using the official Youden's J scoring methodology. + +--- + +## Related + +- [OWASP Benchmark](https://owasp.org/www-project-benchmark/) — the benchmark used for evaluation +- [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) — the base model + +--- + +*teptez-ai is a security research model. Results may vary across codebases and languages. Always have a human analyst review suppressed findings in critical security contexts.* 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..8d5f83f --- /dev/null +++ b/config.json @@ -0,0 +1,62 @@ +{ + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "torch_dtype": "bfloat16", + "eos_token_id": 151645, + "hidden_act": "silu", + "hidden_size": 3584, + "initializer_range": 0.02, + "intermediate_size": 18944, + "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", + 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You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n" +} \ No newline at end of file