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Model: DiTy/gemma-2-9b-it-russian-function-calling-GGUF
Source: Original Platform
---
 .gitattributes                                |   41 +
 README.md                                     |  408 ++++
 config.json                                   |   34 +
 ...-2-9B-it-russian-function-calling-F16.gguf |    3 +
 generation_config.json                        |    8 +
 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                  |  471 ++++
 special_tokens_map.json                       |   34 +
 tokenizer.json                                |    3 +
 tokenizer.model                               |    3 +
 tokenizer_config.json                         | 2013 +++++++++++++++++
 14 files changed, 3030 insertions(+)
 create mode 100644 .gitattributes
 create mode 100644 README.md
 create mode 100644 config.json
 create mode 100644 gemma-2-9B-it-russian-function-calling-F16.gguf
 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 special_tokens_map.json
 create mode 100644 tokenizer.json
 create mode 100644 tokenizer.model
 create mode 100644 tokenizer_config.json

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+gemma-2-9B-it-russian-function-calling-F16.gguf filter=lfs diff=lfs merge=lfs -text
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diff --git a/README.md b/README.md
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+---
+base_model: google/gemma-2-9b-it
+datasets:
+- DiTy/function-calling
+language:
+- ru
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- conversational
+- gemma2
+- function-calling
+- trl
+---
+# DiTy/gemma-2-9b-it-russian-function-calling-GGUF
+
+This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) for the **Function Calling** task on non-synthetic data, 
+fully annotated by humans only, on the Russian version of the <ins>*DiTy/function-calling*</ins> dataset.
+<!-- Provide a quick summary of what the model is/does. -->
+
+In addition to **safetensors**, the model is available in **GGUF** formats (in this case, you need to download only a single file (*[how to inference GGUF model](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#high-level-api)*)):
+
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [gemma-2-9B-it-russian-function-calling-F16.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-russian-function-calling-GGUF/blob/main/gemma-2-9B-it-russian-function-calling-F16.gguf) | F16 | 18.5GB | Base model with float16 |
+
+
+## Model card разделы
+
+* [Как подготовить ваши функции (tools) для *Function Calling*](#prepare_func_call)
+* [Просто используйте chat template для генерации](#just_chat_template)
+* [Prompt структура и ожидаемый контент](#roles)
+* [Оценка моделей под вызов функций](#eval)
+
+## Использование (HuggingFace Transformers)
+
+Ниже представлены некоторые фрагменты кода о том, как быстро приступить к запуску модели. Сначала установите библиотеку Transformers с помощью:
+```bash
+pip install -U transformers
+```
+
+### <a name="prepare_func_call"></a>Как подготовить ваши функции (tools) для *Function Calling*
+
+Вы должны написать функции (инструменты), используемые моделью, в *коде на Python* и обязательно добавить *Python docstrings*, как в примере ниже:
+```python
+def get_weather(city: str):
+    """
+    Функция, которая возвращает погоду в заданном городе.
+    
+    Args:
+        city: Город, для которого надо узнать погоду.
+    """
+    import random
+    
+    return "sunny" if random.random() > 0.5 else "rainy"
+
+
+def get_sunrise_sunset_times(city: str):
+    """
+    Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].
+    
+    Args:
+        city: Город, в котором можно узнать время восхода и захода солнца.
+    """
+
+    return ["6:00", "18:00"]
+```
+
+### <a name="just_chat_template"></a>Просто используйте chat template для генерации
+
+Далее вам нужно загрузить модель и токенизатор:
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+model = AutoModelForCausalLM.from_pretrained(
+    "DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
+    device_map="auto",
+    torch_dtype=torch.bfloat16,  # use float16 or float32 if bfloat16 is not available to you.
+    cache_dir=PATH_TO_MODEL_DIR,  # optional
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
+    cache_dir=PATH_TO_MODEL_DIR,  # optional
+)
+```
+
+Чтобы получить результат генерации, просто используйте `apply_chat_template`. Чтобы учесть наши написанные функции (инструменты), 
+нам нужно передать их в виде списка через атрибут `tools`, а также использовать `add_prompt_generation=True`.
+```python
+history_messages = [
+    {"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
+    {"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"}
+]
+inputs = tokenizer.apply_chat_template(
+    history_messages,
+    tokenize=False,
+    add_generation_prompt=True,  # adding prompt for generation
+    tools=[get_weather, get_sunrise_sunset_times],  # our functions (tools)
+)
+print(inputs)
+```
+
+Тогда наш `inputs` будет выглядеть следующим образом:
+```
+<bos><start_of_turn>user
+Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
+    "name": "get_weather",
+    "description": "Функция, которая возвращает погоду в заданном городе.",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, для которого надо узнать погоду."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+},
+{
+    "name": "get_sunrise_sunset_times",
+    "description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, в котором можно узнать время восхода и захода солнца."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+}
+
+Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
+<start_of_turn>model
+```
+
+Теперь мы можем сгенерировать ответ модели.
+Будьте осторожны, потому что после `apply_chat_template` нет необходимости *добавлять специальные токены* во время токенизации.
+Поэтому используем `add_special_tokens=False`:
+```python
+terminator_ids = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<end_of_turn>"),
+]
+prompt_ids =  tokenizer.encode(inputs, add_special_tokens=False, return_tensors='pt').to(model.device)
+generated_ids = model.generate(
+    prompt_ids,
+    max_new_tokens=512,
+    eos_token_id=terminator_ids,
+    bos_token_id=tokenizer.bos_token_id,
+)
+generated_response = tokenizer.decode(generated_ids[0][prompt_ids.shape[-1]:], skip_special_tokens=False)  # `skip_special_tokens=False` for debug
+print(generated_response)
+```
+
+Мы получаем генерацию в виде вызова функции:
+```
+Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
+```
+
+Отлично, теперь мы можем получать и обрабатывать результаты с помощью нашей *вызываемой функции*, а затем предоставлять модели ответ *функции*:
+```python
+history_messages = [
+    {"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
+    {"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
+    {"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Los Angeles"}}'},
+    {"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'},  # гипотетический ответ от нашей функции
+]
+inputs = tokenizer.apply_chat_template(
+    history_messages,
+    tokenize=False,
+    add_generation_prompt=True,  # добавление запроса для генерации
+    tools=[get_weather, get_sunrise_sunset_times],  # наши функции (tools)
+)
+print(inputs)
+```
+
+Давайте убедимся, что `inputs` верны:
+```
+<bos><start_of_turn>user
+Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
+    "name": "get_weather",
+    "description": "Функция, которая возвращает погоду в заданном городе.",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, для которого надо узнать погоду."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+},
+{
+    "name": "get_sunrise_sunset_times",
+    "description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, в котором можно узнать время восхода и захода солнца."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+}
+
+Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
+<start_of_turn>model
+Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
+<start_of_turn>user
+Ответ от функции: {"times_list": ["6:00", "18:00"]}<end_of_turn>
+<start_of_turn>model
+```
+
+Аналогично, мы генерируем ответ модели:
+```python
+prompt_ids =  tokenizer.encode(inputs, add_special_tokens=False, return_tensors='pt').to(model.device)
+generated_ids = model.generate(
+    prompt_ids,
+    max_new_tokens=512,
+    eos_token_id=terminator_ids,
+    bos_token_id=tokenizer.bos_token_id,
+)
+generated_response = tokenizer.decode(generated_ids[0][prompt_ids.shape[-1]:], skip_special_tokens=False)  # `skip_special_tokens=False` for debug
+print(generated_response)
+```
+
+В результате мы получаем ответ модели:
+```
+В Краснодаре солнце восходит в 6:00 утра и заходит в 18:00 вечера.<end_of_turn>
+```
+
+## Использование через transformers `pipeline`
+
+<details>
+  <summary>
+  Generation via pipeline
+  </summary>
+
+```python
+from transformers import pipeline
+generation_pipeline = pipeline(
+    "text-generation",
+    model="DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
+    model_kwargs={
+        "torch_dtype": torch.bfloat16,  # use float16 or float32 if bfloat16 is not supported for you. 
+        "cache_dir": PATH_TO_MODEL_DIR,  # OPTIONAL
+    },
+    device_map="auto",
+)
+history_messages = [
+    {"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
+    {"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
+    {"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}'},
+    {"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'}
+]
+inputs = generation_pipeline.tokenizer.apply_chat_template(
+    history_messages,
+    tokenize=False,
+    add_generation_prompt=True,
+    tools=[get_weather, get_sunrise_sunset_times],
+)
+terminator_ids = [
+    generation_pipeline.tokenizer.eos_token_id,
+    generation_pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
+]
+outputs = generation_pipeline(
+    inputs,
+    max_new_tokens=512,
+    eos_token_id=terminator_ids,
+)
+print(outputs[0]["generated_text"][len(inputs):])
+```
+  
+</details>
+
+## <a name="roles"></a>Prompt структура и ожидаемый контент
+
+Для наиболее корректной работы модели предполагается, что будет использоваться `apply_chat_template`.
+Необходимо передать историю сообщений в определенном формате.
+```python
+history_messages = [
+    {"role": "...", "content": "..."},
+    ...
+]
+```
+
+Для использования доступны следующие роли:
+
+* `system` - это необязательная роль, ее содержимое всегда размещается в самом начале и перед перечислением функций, доступных модели (инструментов).
+Вы всегда можете воспользоваться стандартным вариантом, который использовался во время обучения: ***"Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "***
+* `user` - запрос пользователя передается через эту роль.
+* `function-call` - тело вызова функции передается через эту роль.
+Хотя модель обучена генерировать вызов функции в виде ***"Вызов функции: {...}\<end_of_turn\>"***, вы все равно должны передать только тело ***"{...}"***
+в поле *"content"*, поскольку используя `apply_chat_template`, постскриптум в инструкциях добавляется автоматически.
+* `function-response` - в этой роли мы должны передать ответ нашей функции в поле *"content"* в виде словаря ***'{"name_returnable_value": value}'***.
+* `model` - содержимое, относящееся к этой роли, считается сгенерированным текстом модели.
+
+
+### Структура истории чата для *Function Calling*
+
+```
+[
+    {"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
+    {"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
+    {"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}'},
+    {"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'}
+]
+```
+
+Это выглядит как:
+```
+<bos><start_of_turn>user
+Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
+    "name": "get_weather",
+    "description": "Функция, которая возвращает погоду в заданном городе.",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, для которого надо узнать погоду."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+},
+{
+    "name": "get_sunrise_sunset_times",
+    "description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "city": {
+                "type": "string",
+                "description": "Город, в котором можно узнать время восхода и захода солнца."
+            }
+        },
+        "required": [
+            "city"
+        ]
+    }
+}
+
+Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
+<start_of_turn>model
+Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
+<start_of_turn>user
+Ответ от функции: {"times_list": ["6:00", "18:00"]}<end_of_turn>
+```
+
+
+### Структура истории чата для обычного user-model шаблона
+
+```
+[
+    {"role": "system", "content": "Ты добрый помощник"},
+    {"role": "user", "content": "Расскажи мне о Москве"}
+]
+```
+
+Это выглядит как:
+```
+<bos><start_of_turn>user
+Ты добрый помощник
+
+Расскажи мне о Москве<end_of_turn>
+```
+
+## <a name="eval"></a>Оценка моделей
+
+В процессе обучения ошибка валидации была приближена к следующим значениям:
+
+| **Model** | **Generation Language** | **Approximately Validation Loss** |
+| :-----: | :-----: | :-----: |
+| [DiTy/gemma-2-27b-it-function-calling-GGUF](https://huggingface.co/DiTy/gemma-2-27b-it-function-calling-GGUF) | EN | 0.47 |
+| [**DiTy/gemma-2-9b-it-russian-function-calling-GGUF**](https://huggingface.co/DiTy/gemma-2-9b-it-russian-function-calling-GGUF) | **RU** | **0.57** |
+| [DiTy/gemma-2-9b-it-function-calling-GGUF](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF) | EN | 0.5 |
+| [DiTy/gemma-2-2b-it-function-calling](https://huggingface.co/DiTy/gemma-2-2b-it-function-calling) | EN | 0.66 |
+
+## Citation
+
+```none
+@article{gemma_2024,
+    title={Gemma},
+    url={https://www.kaggle.com/m/3301},
+    DOI={10.34740/KAGGLE/M/3301},
+    publisher={Kaggle},
+    author={Gemma Team},
+    year={2024}
+}
+```
\ No newline at end of file
diff --git a/config.json b/config.json
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--- /dev/null
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+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
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+  "max_position_embeddings": 8192,
+  "model_type": "gemma2",
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+  "num_hidden_layers": 42,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "sliding_window_size": 4096,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.42.2",
+  "use_cache": true,
+  "vocab_size": 256000
+}
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+  "cache_implementation": "hybrid",
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.42.2"
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+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255997": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255998": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255999": {
+      "content": "<unused99>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": "<bos>",
+  "chat_template": "\n{%- macro render_json(d, indent=4) -%}\n{%- if d is string %}\n{{ '\"' + d + '\"' }}\n{%- elif d is mapping %}\n{%- for key, value in d.items() %}\n{%- if value is string %}\n{{ \" \" * indent + '\"' + key + '\": \"' + value + '\"' }}\n{%- elif value is mapping %}\n{{ \" \" * indent + '\"' + key + '\": {' }}\n{{ render_json(value, indent + 4) }}\n{{ \" \" * indent + \"}\" }}\n{%- elif value is sequence %}\n{{ \" \" * indent + '\"' + key + '\": [\n' }}\n{%- for item in value %}\n{{- \" \" * (indent + 4) + render_json(item, indent + 4) }}\n{%- if not loop.last %},\n{% endif %}\n{%- endfor %}\n{{ '\n' + \" \" * indent + \"]\" }}\n{%- else %}\n{{ \" \" * indent + '\"' + key + '\": ' + value|string }}\n{%- endif %}\n{%- if not loop.last %},\n{% endif %}\n{%- endfor %}\n{%- elif d is sequence %}\n{%- for item in d %}\n{{ \" \" * indent + render_json(item, indent + 4) }}\n{%- if not loop.last %},\n{% endif %}\n{%- endfor %}\n{%- else %}\n{{ \" \" * indent + d|string }}\n{%- endif %}\n{%- endmacro %}\n\n\n{#- This block checks system prompt and list of tools #}\n{%- if not add_generation_prompt is defined %}\n    {%- set add_generation_prompt = false %}\n{%- endif %}\n{%- if messages[0][\"role\"] == \"system\" %}\n    {%- set system_message = messages[0][\"content\"] %}\n    {%- set loop_messages = messages[1:] %}\n{%- else %}\n    {%- set loop_messages = messages %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n{%- set user_messages = loop_messages | selectattr(\"role\", \"equalto\", \"user\") | list %}\n\n\n{#- This block checks for alternating user/model messages, skipping tool calling messages #}\n{%- set ns = namespace() %}\n{%- set ns.index = 0 %}\n{%- for message in loop_messages %}\n    {%- if (message[\"role\"] == \"user\" or message[\"role\"] == \"function-response\") != (ns.index % 2 == 0) %}\n        {{- raise_exception(\"After the optional system message, conversation roles must alternate user/model/user/model/... NB: 'function-call' is same as the 'model' and 'function-response' is same as the 'user'!\") }}\n    {%- endif %}\n    {%- set ns.index = ns.index + 1 %}\n{%- endfor %}\n\n\n{#- This block format full dialogue messages #}\n{{- bos_token }}\n{{- \"<start_of_turn>user\" + '\n' }}\n{%- if system_message != \"\" %}\n    {{- system_message }}\n{%- endif %}\n{%- if tools is not none %}\n    {%- for tool in tools %}\n        {%- set tool = tool.function %}\n        {{- '{\n' }}\n        {{- render_json(tool, 4) }}\n        {%- if not loop.last %}\n            {{- \"\n},\n\" }}\n        {%- else %}\n            {{- \"\n}\n\" }}\n        {% endif %}\n    {%- endfor %}\n    {%- elif system_message != \"\" %}\n        {{- '\n\n' }}\n{%- endif %}\n{{ loop_messages[0]['content'] + '<end_of_turn>\n' }}\n{%- for message in loop_messages[1:] %}\n    {%- if message[\"role\"] == \"user\" %}\n        {{- \"<start_of_turn>user\" + '\n' + message['content'] + '<end_of_turn>\n' }}\n    {%- elif message[\"role\"] == \"model\" %}\n        {{- \"<start_of_turn>model\" + '\n' + message['content'] + '<end_of_turn>\n' }}\n    {%- elif message[\"role\"] == \"function-call\" %}\n        {{- \"<start_of_turn>model\" + '\n' + \"Вызов функции: \" + message['content'] + '<end_of_turn>\n' }}\n    {%- elif message[\"role\"] == \"function-response\" %}\n        {{- \"<start_of_turn>user\" + '\n' + \"Ответ от функции: \" + message['content'] + '<end_of_turn>\n' }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {%- if loop_messages[-1]['role'] == \"user\" or loop_messages[-1]['role'] == \"function-response\" %}\n{{ '<start_of_turn>model\n' }}\n    {%- else %}\n        {{- raise_exception(\"For add_generation_prompt=True, the last message role must be 'user' or 'function-response'.\") }}\n    {%- endif %}\n{%- endif %}\n\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}