Add s1-mini v075

.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

LICENSE

@@ -0,0 +1,201 @@
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README.md

@@ -1,3 +1,202 @@
 ---
-license: mit
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+library_name: transformers
+pipeline_tag: text-generation
+language:
+  - en
+tags:
+  - asr
+  - text-normalization
+  - speech-to-text
+  - post-processing
+  - qwen3
 ---
+
+# s1-mini
+
+A 0.6B-parameter text normalizer for speech-to-text output. It takes a raw ASR
+transcript and rewrites it as clean written text: fillers removed, false starts
+and self-corrections resolved to the value the speaker landed on, punctuation
+and capitalization applied, and spoken numbers, dates, times, currency, phone
+numbers and email addresses rendered in written form.
+
+On a held-out set of 6,183 English cases it reaches 94.4% token accuracy at a
+perplexity of 1.228. Quantized it is 462 MB and runs on a laptop CPU.
+
+Release v075. English only. It is not a chat model and will not follow general
+instructions. It does one job, and you steer it with a control line at the top
+of the input.
+
+Fine-tuned from [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) with
+LoRA, then merged. If you want to run it in llama.cpp, Ollama or LM Studio,
+grab the GGUF builds from
+[superwhisper/s1-mini-GGUF](https://huggingface.co/superwhisper/s1-mini-GGUF).
+
+Releases are tagged, so you can pin one:
+`from_pretrained("superwhisper/s1-mini", revision="v075")`.
+
+## Files
+
+| File | Contents |
+|---|---|
+| `model.safetensors` | 311 weight tensors, BF16, LoRA already merged into the base. 1.4 GB. |
+| `config.json` | Qwen3 architecture: 28 layers, hidden size 1024, 16 attention heads over 8 KV heads, 40,960 max positions. |
+| `generation_config.json` | Decoding defaults. Greedy (`do_sample: false`), EOS `151645`/`151643`. |
+| `tokenizer.json` | The BPE tokenizer, 151,936 tokens. Unmodified from Qwen3. |
+| `vocab.json`, `merges.txt` | Vocabulary and merge ranks the tokenizer is built from. |
+| `tokenizer_config.json` | Special tokens and tokenizer settings. |
+| `chat_template.jinja` | The Jinja prompt template. Qwen3's, unchanged, which is why `enable_thinking=False` matters. |
+
+## You have to include the control line
+
+Every input starts with a control line, then a newline, then the transcript.
+Skip it and you'll get poor output, because the model was never trained to
+guess these settings.
+
+```
+[Styling: <value>] [Structure: <value>] [Context: <value>]
+<raw transcript>
+```
+
+| Axis | Values | What it does |
+|---|---|---|
+| `Styling` | `casual`, `semi-casual`, `semi-formal`, `formal` | Sets the register. `casual` capitalizes nothing and only adds punctuation the speaker actually dictated. `formal` expands contractions and punctuates everything. |
+| `Structure` | `prose`, `lists` | Whether the model may break enumerable content into a bulleted list. It needs at least three items, and anything that isn't really a list stays as prose. |
+| `Context` | `general`, `email` | Destination conventions. `email` turns on greeting-line and sign-off-block layout. |
+
+The three axes are independent and every combination was trained.
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+MODEL = "superwhisper/s1-mini"
+
+tok = AutoTokenizer.from_pretrained(MODEL)
+model = AutoModelForCausalLM.from_pretrained(MODEL, torch_dtype=torch.bfloat16, device_map="auto")
+
+SYSTEM = (
+    "You are a text normalizer for speech-to-text transcripts. The input begins "
+    "with a control line specifying the styling, structure, and context settings; "
+    "clean the transcript to match those settings and output only the cleaned text."
+)
+
+def normalize(transcript, styling="semi-formal", structure="prose", context="general"):
+    control = f"[Styling: {styling}] [Structure: {structure}] [Context: {context}]"
+    messages = [
+        {"role": "system", "content": SYSTEM},
+        {"role": "user", "content": f"{control}\n{transcript}"},
+    ]
+    text = tok.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True,
+        enable_thinking=False,      # required, see below
+    )
+    inputs = tok(text, return_tensors="pt").to(model.device)
+    out = model.generate(**inputs, max_new_tokens=1024, do_sample=False)
+    return tok.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+
+
+raw = "so um i need to like send the the report by uh friday no wait make that thursday"
+print(normalize(raw))
+# The report needs to be sent by Thursday.
+```
+
+### Set `enable_thinking=False`
+
+The chat template comes from Qwen3 unchanged, and Qwen3 turns on thinking mode
+by default. s1-mini was trained with thinking off and has no reasoning traces
+in its training data, so if you leave the flag out you'll get output wrapped in
+`<think>` tags.
+
+The flag makes the template emit an empty think block (`<think>\n\n</think>`)
+before the assistant turn. That's the exact prefix the model saw during
+training, so if you build prompts by hand instead of using the template, include
+it.
+
+### Decoding
+
+`generation_config.json` ships greedy, with `do_sample: false`. Normalization
+is a deterministic transformation, and sampling only adds variance. The numbers
+below were measured greedy. If you override the config, use temperature 0.
+
+## Results
+
+Held-out English test set of 6,183 cases, covering real ASR output (GigaSpeech
+through Parakeet, plus podcast and lecture transcripts) and synthetic stress
+sets for numbers, self-corrections, lists, email and adversarial inputs.
+
+| Metric | Value |
+|---|---|
+| Token accuracy | 94.4% |
+| Perplexity | 1.228 |
+| TER | 0.146 |
+| Correct empty output | 99.3% (143/144) |
+
+Some inputs are pure filler or background noise, where the correct output is an
+empty string. The model returns one in 143 of the 144 such cases rather than
+producing text.
+
+On structure, across 6,039 cases it agrees with the reference on whether the
+output should be a list 96.3% of the time, and it adds list formatting to plain
+prose in 0.4% of cases. It leans toward prose: under `Structure: lists` it only
+breaks text up when the enumeration is unmistakable, so borderline content comes
+back as paragraphs.
+
+On the 430 email cases it places the greeting line correctly 99.1% of the time
+and the sign-off block 96.7%.
+
+These numbers come from the Q4_K_M GGUF build, so they reflect the quantized
+model. The BF16 weights here should do at least as well.
+
+## Limitations
+
+- **Email vertical spacing needs a second pass.** Greeting and sign-off
+  detection are strong, but blank-line placement agrees with the reference
+  about 72% of the time. If exact spacing matters, post-process it.
+- **English only.** About 5% of the training mix was non-English YouTube
+  material, so the model will produce something for other languages, but that
+  data was cleaned under English style rules, no language-specific rules were
+  ever trained, and no non-English output has been reviewed by a speaker of the
+  language. Don't rely on it outside English.
+- **Only `general` and `email` contexts exist.** Chat, notes and code
+  destinations aren't trained yet.
+- **Casual is the hardest register**, especially where casual styling meets
+  email layout.
+- **Long inputs are out of distribution.** Training packed to 1,024 tokens.
+
+## Training
+
+| | |
+|---|---|
+| Base | Qwen/Qwen3-0.6B |
+| Method | LoRA (r=16, α=32, dropout 0.05), merged into the base |
+| Target modules | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` |
+| Examples | 189,717 |
+| Steps | 2,277 (1 epoch) |
+| Learning rate | 4e-4 |
+| Effective batch | 32 (16 × 2 grad accum) |
+| Max sequence length | 1,024, packed |
+| Loss | Assistant tokens only |
+| Precision | BF16 |
+| Hardware | 1× H100 |
+
+Final training loss 0.062, best held-out validation loss 0.169.
+
+The training targets were made by cleaning ASR transcripts with a large
+language model working from an explicit written rule set, then running the
+results through automated style and content-fidelity checks. Sources include
+GigaSpeech audio transcribed with Parakeet, YouTube transcripts, short-form
+dictation, and several synthetic corpora built specifically for numbers,
+self-corrections, lists, email and adversarial inputs.
+
+GigaSpeech-derived material carries its own upstream usage terms. Those apply
+to the training data, not to these weights.
+
+## License
+
+Apache 2.0, inherited from Qwen3-0.6B.

chat_template.jinja

@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,30 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "max_position_embeddings": 40960,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+    "bos_token_id": 151643,
+    "do_sample": false,
+    "eos_token_id": [
+        151645,
+        151643
+    ],
+    "pad_token_id": 151643,
+    "transformers_version": "4.51.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd4cb00397d0798f39bb8caac13029ed6150a5a661c91c087aa42ab193c0c5e6
+size 1503300328

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
+size 11422654

tokenizer_config.json

@@ -0,0 +1,239 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_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|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\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>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\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\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].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\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\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        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\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    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}