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- README.md +290 -0
- chat_template.jinja +154 -0
- config.json +103 -0
- model.safetensors-00001-of-00001.safetensors +3 -0
- model.safetensors.index.json +639 -0
- preprocessor_config.json +21 -0
- tokenizer.json +3 -0
- tokenizer_config.json +32 -0
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| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
language:
|
| 4 |
+
- en
|
| 5 |
+
base_model: Qwen/Qwen3.5-2B
|
| 6 |
+
tags:
|
| 7 |
+
- tool-output-pruning
|
| 8 |
+
- context-engineering
|
| 9 |
+
- context-pruning
|
| 10 |
+
- code-agent
|
| 11 |
+
- squeez
|
| 12 |
+
- qwen3.5
|
| 13 |
+
pipeline_tag: text-generation
|
| 14 |
+
library_name: transformers
|
| 15 |
+
datasets:
|
| 16 |
+
- KRLabsOrg/tool-output-extraction-swebench
|
| 17 |
+
---
|
| 18 |
+
|
| 19 |
+
<p align="center">
|
| 20 |
+
<img src="https://github.com/KRLabsOrg/squeez/blob/main/assets/squeez_mascot.png?raw=true" alt="Squeez" width="250"/>
|
| 21 |
+
<br><em>Squeeze out the juice, leave the pulp behind.</em>
|
| 22 |
+
</p>
|
| 23 |
+
|
| 24 |
+
# Squeez-2B
|
| 25 |
+
|
| 26 |
+
LLM coding agents spend **80-95% of their context window** on irrelevant tool output — passing test names, boilerplate headers, unchanged files. Squeez reads the raw output alongside a task description and returns **only the lines the agent needs to read next**, compressing tool output by ~91% on average while keeping 86% of the relevant information.
|
| 27 |
+
|
| 28 |
+
Unlike keyword search (BM25) or generic semantic highlighting, Squeez is trained specifically on tool output from real software engineering workflows — test logs, grep results, build errors, git diffs, stack traces, and more.
|
| 29 |
+
|
| 30 |
+
## What is Squeez?
|
| 31 |
+
|
| 32 |
+
Squeez is a **tool output pruner for coding agents**. When an agent runs a tool (pytest, grep, git log, npm build, kubectl, etc.), the output is often hundreds of lines — but only a handful matter for the current task. Squeez acts as a filter between the tool and the agent's context window:
|
| 33 |
+
|
| 34 |
+
```
|
| 35 |
+
Tool output (500 lines) → Squeez → Relevant lines (30 lines) → Agent context
|
| 36 |
+
```
|
| 37 |
+
|
| 38 |
+
This model (Squeez-2B) is a generative approach: [Qwen 3.5 2B](https://huggingface.co/Qwen/Qwen3.5-2B) fine-tuned to extract verbatim relevant lines from tool output, given a task-specific query.
|
| 39 |
+
|
| 40 |
+
### Why a small fine-tuned model?
|
| 41 |
+
|
| 42 |
+
- **Fast**: 2B parameters — runs on a single GPU or even CPU, serves via vLLM at high throughput
|
| 43 |
+
- **Accurate**: Outperforms a 35B MoE model (Qwen 3.5 35B A3B) at zero-shot by **+13% Span F1**
|
| 44 |
+
- **Faithful**: Returns verbatim lines only — no rewriting, no hallucination, no summarization
|
| 45 |
+
- **Drop-in**: Works as a CLI pipe, Python library, or vLLM server — integrates with any agent framework
|
| 46 |
+
|
| 47 |
+
## Evaluation
|
| 48 |
+
|
| 49 |
+
Evaluated on 617 held-out test samples from SWE-bench repositories, across 14 tool types:
|
| 50 |
+
|
| 51 |
+
### Squeez-2B vs. generative models
|
| 52 |
+
|
| 53 |
+
| Model | Span P | Span R | Span F1 | Exact Match | Fuzzy F1 | Partial Overlap | Empty Acc | ROUGE-L | Compression |
|
| 54 |
+
|-------|--------|--------|---------|-------------|----------|-----------------|-----------|---------|-------------|
|
| 55 |
+
| **Squeez-2B** | **0.8043** | **0.8624** | **0.7895** | **0.4911** | **0.8035** | **0.9189** | **0.9676** | **0.7208** | 0.9150 |
|
| 56 |
+
| Qwen 3.5 35B A3B (zero-shot) | 0.7402 | 0.7498 | 0.7000 | 0.3922 | 0.7254 | 0.8347 | 0.9157 | 0.7151 | 0.9177 |
|
| 57 |
+
| Qwen 3.5 2B (untrained) | 0.4154 | 0.5299 | 0.4075 | 0.1945 | 0.5482 | 0.7683 | 0.9157 | 0.5481 | 0.8197 |
|
| 58 |
+
|
| 59 |
+
### Squeez-2B vs. naive baselines
|
| 60 |
+
|
| 61 |
+
| Model | Span P | Span R | Span F1 | Exact Match | Fuzzy F1 | Partial Overlap | Empty Acc | ROUGE-L | Compression |
|
| 62 |
+
|-------|--------|--------|---------|-------------|----------|-----------------|-----------|---------|-------------|
|
| 63 |
+
| **Squeez-2B** | **0.8043** | **0.8624** | **0.7895** | **0.4911** | **0.8035** | **0.9189** | **0.9676** | **0.7208** | 0.9150 |
|
| 64 |
+
| BM25 (10%) | 0.1277 | 0.2172 | 0.1314 | 0.0146 | 0.2314 | 0.5883 | 0.8981 | 0.2073 | 0.9036 |
|
| 65 |
+
| First-N (10%) | 0.0741 | 0.1445 | 0.0798 | 0.0194 | 0.1570 | 0.4389 | 0.9175 | 0.1370 | 0.9055 |
|
| 66 |
+
| Random (10%) | 0.0738 | 0.1009 | 0.0697 | 0.0113 | 0.1966 | 0.4984 | 0.9061 | 0.1397 | 0.9067 |
|
| 67 |
+
| Last-N (10%) | 0.0496 | 0.0503 | 0.0407 | 0.0129 | 0.1393 | 0.3916 | 0.8560 | 0.1173 | 0.9130 |
|
| 68 |
+
|
| 69 |
+
### Metric definitions
|
| 70 |
+
|
| 71 |
+
- **Span F1**: strict line-level set overlap between predicted and gold relevant lines
|
| 72 |
+
- **Fuzzy F1**: same as Span F1 but with fuzzy substring matching (threshold 0.5)
|
| 73 |
+
- **Partial Overlap**: fraction of gold lines that have any overlap with predictions
|
| 74 |
+
- **Empty Accuracy**: correctly predicting empty vs non-empty output (tool returned nothing relevant)
|
| 75 |
+
- **Compression**: fraction of input removed (higher = more aggressive pruning)
|
| 76 |
+
|
| 77 |
+
## Quick Start
|
| 78 |
+
|
| 79 |
+
### With vLLM (recommended)
|
| 80 |
+
|
| 81 |
+
```bash
|
| 82 |
+
# Start the server
|
| 83 |
+
pip install vllm
|
| 84 |
+
vllm serve KRLabsOrg/squeez-2b --dtype bfloat16 --max-model-len 16384
|
| 85 |
+
|
| 86 |
+
# Use from squeez CLI
|
| 87 |
+
pip install squeez
|
| 88 |
+
export SQUEEZ_SERVER_URL=http://localhost:8000/v1
|
| 89 |
+
cat output.txt | squeez "find the bug"
|
| 90 |
+
|
| 91 |
+
# Or pipe directly
|
| 92 |
+
python -m pytest tests/ -v 2>&1 | squeez "find the test failure related to authentication"
|
| 93 |
+
```
|
| 94 |
+
|
| 95 |
+
vLLM gives you batched inference, continuous batching, and high throughput — ideal when multiple agents or tools are running concurrently.
|
| 96 |
+
|
| 97 |
+
### With squeez (local, no server)
|
| 98 |
+
|
| 99 |
+
```bash
|
| 100 |
+
pip install squeez
|
| 101 |
+
|
| 102 |
+
# Downloads and runs the model locally (no GPU server needed)
|
| 103 |
+
squeez "Find the failing traceback block" --input-file output.txt
|
| 104 |
+
```
|
| 105 |
+
|
| 106 |
+
> **Note:** Local mode loads the model on every call. Fine for one-off use, but for repeated calls (e.g. an agent piping every tool through squeez), use vLLM — the model stays warm in memory.
|
| 107 |
+
|
| 108 |
+
### With transformers
|
| 109 |
+
|
| 110 |
+
```python
|
| 111 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 112 |
+
import torch
|
| 113 |
+
|
| 114 |
+
model_name = "KRLabsOrg/squeez-2b"
|
| 115 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
|
| 116 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 117 |
+
model_name,
|
| 118 |
+
torch_dtype=torch.bfloat16,
|
| 119 |
+
device_map="auto",
|
| 120 |
+
trust_remote_code=True,
|
| 121 |
+
)
|
| 122 |
+
|
| 123 |
+
messages = [
|
| 124 |
+
{"role": "system", "content": (
|
| 125 |
+
"You prune verbose tool output for a coding agent. "
|
| 126 |
+
"Given a focused extraction query and one tool output, return only the "
|
| 127 |
+
"smallest verbatim evidence block(s) the agent should read next. "
|
| 128 |
+
"Return the kept text inside <relevant_lines> tags. "
|
| 129 |
+
"Do not rewrite, summarize, or invent lines."
|
| 130 |
+
)},
|
| 131 |
+
{"role": "user", "content": (
|
| 132 |
+
"<query>\nFix the failing authentication test\n</query>\n"
|
| 133 |
+
"<tool_output>\n"
|
| 134 |
+
"PASSED tests/test_login.py::test_valid_credentials\n"
|
| 135 |
+
"FAILED tests/test_login.py::test_token_refresh - AssertionError: expected 200 got 401\n"
|
| 136 |
+
"PASSED tests/test_login.py::test_logout\n"
|
| 137 |
+
"PASSED tests/test_login.py::test_rate_limiting\n"
|
| 138 |
+
"\n</tool_output>"
|
| 139 |
+
)},
|
| 140 |
+
]
|
| 141 |
+
|
| 142 |
+
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
| 143 |
+
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
|
| 144 |
+
|
| 145 |
+
with torch.no_grad():
|
| 146 |
+
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1, do_sample=True)
|
| 147 |
+
|
| 148 |
+
response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
|
| 149 |
+
print(response)
|
| 150 |
+
```
|
| 151 |
+
|
| 152 |
+
**Output:**
|
| 153 |
+
```xml
|
| 154 |
+
<relevant_lines>
|
| 155 |
+
FAILED tests/test_login.py::test_token_refresh - AssertionError: expected 200 got 401
|
| 156 |
+
</relevant_lines>
|
| 157 |
+
```
|
| 158 |
+
|
| 159 |
+
### Python API (with squeez)
|
| 160 |
+
|
| 161 |
+
```python
|
| 162 |
+
from squeez.inference.extractor import ToolOutputExtractor
|
| 163 |
+
|
| 164 |
+
# Loads this model locally
|
| 165 |
+
extractor = ToolOutputExtractor(model_path="KRLabsOrg/squeez-2b")
|
| 166 |
+
|
| 167 |
+
# Or connect to a vLLM server
|
| 168 |
+
extractor = ToolOutputExtractor(base_url="http://localhost:8000/v1")
|
| 169 |
+
|
| 170 |
+
filtered = extractor.extract(
|
| 171 |
+
task="Find the referer validation block",
|
| 172 |
+
tool_output=raw_output,
|
| 173 |
+
)
|
| 174 |
+
print(filtered)
|
| 175 |
+
```
|
| 176 |
+
|
| 177 |
+
## Input / Output Format
|
| 178 |
+
|
| 179 |
+
**Input** — chat format with system prompt:
|
| 180 |
+
|
| 181 |
+
```
|
| 182 |
+
System: You prune verbose tool output for a coding agent. Given a focused
|
| 183 |
+
extraction query and one tool output, return only the smallest verbatim
|
| 184 |
+
evidence block(s) the agent should read next. Return the kept text inside
|
| 185 |
+
<relevant_lines> tags. Do not rewrite, summarize, or invent lines.
|
| 186 |
+
|
| 187 |
+
User: <query>{task_description}</query>
|
| 188 |
+
<tool_output>{raw_tool_output}</tool_output>
|
| 189 |
+
```
|
| 190 |
+
|
| 191 |
+
**Output** — verbatim relevant lines wrapped in XML:
|
| 192 |
+
|
| 193 |
+
```xml
|
| 194 |
+
<relevant_lines>
|
| 195 |
+
{only the lines that matter, copied verbatim}
|
| 196 |
+
</relevant_lines>
|
| 197 |
+
```
|
| 198 |
+
|
| 199 |
+
If no lines are relevant, the model returns empty tags: `<relevant_lines>\n</relevant_lines>`.
|
| 200 |
+
|
| 201 |
+
## Supported Tool Types
|
| 202 |
+
|
| 203 |
+
The model was trained on 14 tool types from SWE-bench repositories:
|
| 204 |
+
|
| 205 |
+
| Tool type | Description | Example |
|
| 206 |
+
|-----------|-------------|---------|
|
| 207 |
+
| `test_output` | pytest / unittest output | Test failures, tracebacks, assertion errors |
|
| 208 |
+
| `read_file` | File contents | Source code, config files |
|
| 209 |
+
| `grep` | Search results | Pattern matches across files |
|
| 210 |
+
| `git_diff` | Code changes | Diffs between commits or branches |
|
| 211 |
+
| `git_log` | Commit history | Relevant commits |
|
| 212 |
+
| `git_blame` | Line-level attribution | Who changed what |
|
| 213 |
+
| `ls` | Directory listings | File structure |
|
| 214 |
+
| `python` | Python REPL output | Script output, errors |
|
| 215 |
+
| `curl` | HTTP responses | API responses, documentation |
|
| 216 |
+
| `build_output` | Build logs | Compilation errors, warnings |
|
| 217 |
+
| `lint_output` | Linter output | Style/type violations |
|
| 218 |
+
| `pip_install` | Package manager output | Dependency errors |
|
| 219 |
+
| `type_check` | Type checker output | mypy/pyright errors |
|
| 220 |
+
| `coverage` | Coverage reports | Uncovered lines |
|
| 221 |
+
|
| 222 |
+
## Training Details
|
| 223 |
+
|
| 224 |
+
| Parameter | Value |
|
| 225 |
+
|-----------|-------|
|
| 226 |
+
| Base model | [Qwen/Qwen3.5-2B](https://huggingface.co/Qwen/Qwen3.5-2B) |
|
| 227 |
+
| Fine-tuning method | LoRA (r=16, alpha=32) via [Unsloth](https://github.com/unslothai/unsloth) |
|
| 228 |
+
| Training data | Squeez v3 — 10,508 samples from [SWE-bench](https://swe-bench.github.io/) |
|
| 229 |
+
| Epochs | 3 (best checkpoint at epoch 1.5) |
|
| 230 |
+
| Max sequence length | 16,384 tokens |
|
| 231 |
+
| Learning rate | 2e-4 |
|
| 232 |
+
| Batch size | 8 (effective 32 with 4x gradient accumulation) |
|
| 233 |
+
| Warmup | 5% of steps |
|
| 234 |
+
| Weight decay | 0.01 |
|
| 235 |
+
| Checkpoint selection | Best validation Span F1 |
|
| 236 |
+
|
| 237 |
+
### Data generation
|
| 238 |
+
|
| 239 |
+
Training data was generated by running 14 types of tool calls on SWE-bench repositories and using a teacher model to label the relevant lines. Each sample contains:
|
| 240 |
+
- A focused extraction query (what the agent needs to find)
|
| 241 |
+
- Raw tool output (as the agent would see it)
|
| 242 |
+
- Gold relevant lines (the minimal set the agent should read)
|
| 243 |
+
|
| 244 |
+
Dataset: [KRLabsOrg/tool-output-extraction-swebench](https://huggingface.co/datasets/KRLabsOrg/tool-output-extraction-swebench)
|
| 245 |
+
|
| 246 |
+
## Limitations
|
| 247 |
+
|
| 248 |
+
- Trained primarily on Python/SWE-bench data — works best on software engineering tool output, though the prompt format generalizes to other domains
|
| 249 |
+
- Not designed for general-purpose text summarization or question answering
|
| 250 |
+
- Very short outputs (<5 lines) may be returned unchanged
|
| 251 |
+
- Max input length is 16,384 tokens — longer outputs should be chunked
|
| 252 |
+
|
| 253 |
+
## Use with coding agents
|
| 254 |
+
|
| 255 |
+
Add to your agent's system instructions (e.g. `CLAUDE.md` for Claude Code):
|
| 256 |
+
|
| 257 |
+
```
|
| 258 |
+
Always pipe shell commands through squeez and tell exactly what you want to know.
|
| 259 |
+
|
| 260 |
+
Examples:
|
| 261 |
+
- `bun test 2>&1 | squeez "did the tests pass?"`
|
| 262 |
+
- `git log --oneline -50 | squeez "find the commit that broke CSRF"`
|
| 263 |
+
- `cat src/auth/middleware.py | squeez "find the referer validation logic"`
|
| 264 |
+
|
| 265 |
+
Do NOT use squeez when:
|
| 266 |
+
- You need exact, uncompressed output (e.g. writing a patch)
|
| 267 |
+
- The command is interactive
|
| 268 |
+
```
|
| 269 |
+
|
| 270 |
+
## Citation
|
| 271 |
+
|
| 272 |
+
```bibtex
|
| 273 |
+
@software{kovacs2026squeez,
|
| 274 |
+
title={Squeez: Compressing Tool Output for LLM Coding Agents},
|
| 275 |
+
author={Adam Kovacs},
|
| 276 |
+
year={2026},
|
| 277 |
+
url={https://github.com/KRLabsOrg/squeez}
|
| 278 |
+
}
|
| 279 |
+
```
|
| 280 |
+
|
| 281 |
+
## License
|
| 282 |
+
|
| 283 |
+
Apache 2.0
|
| 284 |
+
|
| 285 |
+
## Acknowledgments
|
| 286 |
+
|
| 287 |
+
- [Qwen](https://huggingface.co/Qwen) for the Qwen 3.5 2B base model
|
| 288 |
+
- [Unsloth](https://github.com/unslothai/unsloth) for efficient LoRA training
|
| 289 |
+
- [SWE-bench](https://swe-bench.github.io/) for the evaluation framework and source repositories
|
| 290 |
+
- [Provence](https://arxiv.org/abs/2501.16214) and [SWE-Pruner](https://github.com/ayanami-kitasan/SWE-Pruner) for inspiration on context pruning approaches
|
chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is true %}
|
| 150 |
+
{{- '<think>\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,103 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
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|
| 6 |
+
"image_token_id": 248056,
|
| 7 |
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"model_name": "Qwen/Qwen3.5-2B",
|
| 8 |
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|
| 9 |
+
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|
| 10 |
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|
| 11 |
+
"attention_bias": false,
|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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"linear_attention",
|
| 25 |
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"linear_attention",
|
| 26 |
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"linear_attention",
|
| 27 |
+
"full_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
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"full_attention",
|
| 32 |
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"linear_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
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"linear_attention",
|
| 35 |
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"full_attention",
|
| 36 |
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"linear_attention",
|
| 37 |
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"linear_attention",
|
| 38 |
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"linear_attention",
|
| 39 |
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"full_attention",
|
| 40 |
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"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"full_attention",
|
| 44 |
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"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
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"linear_attention",
|
| 47 |
+
"full_attention"
|
| 48 |
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],
|
| 49 |
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|
| 50 |
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"linear_key_head_dim": 128,
|
| 51 |
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"linear_num_key_heads": 16,
|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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"mlp_only_layers": [],
|
| 57 |
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|
| 58 |
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|
| 59 |
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"mtp_use_dedicated_embeddings": false,
|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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"rope_parameters": {
|
| 67 |
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"mrope_interleaved": true,
|
| 68 |
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"mrope_section": [
|
| 69 |
+
11,
|
| 70 |
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11,
|
| 71 |
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10
|
| 72 |
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],
|
| 73 |
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"partial_rotary_factor": 0.25,
|
| 74 |
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"rope_theta": 10000000,
|
| 75 |
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"rope_type": "default"
|
| 76 |
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},
|
| 77 |
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"tie_word_embeddings": true,
|
| 78 |
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"use_cache": true,
|
| 79 |
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"vocab_size": 248320
|
| 80 |
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},
|
| 81 |
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|
| 82 |
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"unsloth_version": "2026.3.4",
|
| 83 |
+
"video_token_id": 248057,
|
| 84 |
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"vision_config": {
|
| 85 |
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"deepstack_visual_indexes": [],
|
| 86 |
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"depth": 24,
|
| 87 |
+
"torch_dtype": "bfloat16",
|
| 88 |
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"hidden_act": "gelu_pytorch_tanh",
|
| 89 |
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"hidden_size": 1024,
|
| 90 |
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"in_channels": 3,
|
| 91 |
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"initializer_range": 0.02,
|
| 92 |
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"intermediate_size": 4096,
|
| 93 |
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"model_type": "qwen3_5",
|
| 94 |
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"num_heads": 16,
|
| 95 |
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"num_position_embeddings": 2304,
|
| 96 |
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"out_hidden_size": 2048,
|
| 97 |
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"patch_size": 16,
|
| 98 |
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"spatial_merge_size": 2,
|
| 99 |
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"temporal_patch_size": 2
|
| 100 |
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|
| 101 |
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"vision_end_token_id": 248054,
|
| 102 |
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"vision_start_token_id": 248053
|
| 103 |
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}
|
model.safetensors-00001-of-00001.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:390a6b651c6ee0cb7e1d10636056cba492154b52d8204a8fa0f05e904930c0bf
|
| 3 |
+
size 4548221488
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,639 @@
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
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|
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|
| 639 |
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preprocessor_config.json
ADDED
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{
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"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"image_processor_type": "Qwen2VLImageProcessorFast"
|
| 21 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
|
| 3 |
+
size 19989343
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|im_end|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>",
|
| 31 |
+
"chat_template": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n {%- if content is string %}\n {{- content }}\n {%- elif content is iterable and content is not mapping %}\n {%- for item in content %}\n {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain images.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set image_count.value = image_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Picture ' ~ image_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n {%- elif 'video' in item or item.type == 'video' %}\n {%- if is_system_content %}\n {{- raise_exception('System message cannot contain videos.') }}\n {%- endif %}\n {%- if do_vision_count %}\n {%- set video_count.value = video_count.value + 1 %}\n {%- endif %}\n {%- if add_vision_id %}\n {{- 'Video ' ~ video_count.value ~ ': ' }}\n {%- endif %}\n {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n {%- elif 'text' in item %}\n {{- item.text }}\n {%- else %}\n {{- raise_exception('Unexpected item type in content.') }}\n {%- endif %}\n {%- endfor %}\n {%- elif content is none or content is undefined %}\n {{- '' }}\n {%- else %}\n {{- raise_exception('Unexpected content type.') }}\n {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n {{- '<|im_start|>system\\n' }}\n {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\" }}\n {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {%- if content %}\n {{- '\\n\\n' + content }}\n {%- endif %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {%- set content = render_content(messages[0].content, false, true)|trim %}\n {{- '<|im_start|>system\\n' + content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" %}\n {%- set content = render_content(message.content, false)|trim %}\n {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n {%- set content = render_content(message.content, true)|trim %}\n {%- if message.role == \"system\" %}\n {%- if not loop.first %}\n {{- raise_exception('System message must be at the beginning.') }}\n {%- endif %}\n {%- elif message.role == \"user\" %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- set reasoning_content = reasoning_content|trim %}\n {%- if loop.index0 > ns.last_query_index %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\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 {%- if loop.first %}\n {%- if content|trim %}\n {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- else %}\n {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- else %}\n {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n {%- endif %}\n {%- if tool_call.arguments is defined %}\n {%- for args_name, args_value in tool_call.arguments|items %}\n {{- '<parameter=' + args_name + '>\\n' }}\n {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}\n {{- args_value }}\n {{- '\\n</parameter>\\n' }}\n {%- endfor %}\n {%- endif %}\n {{- '</function>\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n {{- '<|im_end|>\\n' }}\n {%- elif loop.last %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- else %}\n {{- raise_exception('Unexpected message role.') }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is true %}\n {{- '<think>\\n' }}\n {%- else %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}"
|
| 32 |
+
}
|