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Model: ai9stars/G9v3-3B Source: Original Platform
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119
README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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- zh
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- g9v3
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- llama
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- text-generation
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- long-context
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- tool-calling
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---
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<div align="center">
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<h1>G9v3-3B</h1>
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</div>
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<p align="center">
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<a href="https://github.com/AI9Stars" target="_blank">GitHub</a> |
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<a href="https://huggingface.co/ai9stars" target="_blank">Hugging Face</a>
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</p>
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## Introduction
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**G9v3-3B** is a dense 3B causal language model from the **AI9Stars** team, built for local deployment and resource-constrained scenarios. It targets everyday assistant use, coding, tool-use workflows, and reasoning tasks where a compact model is preferred.
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## Model Information
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- **Type**: Causal Language Model
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- **Architecture**: Standard `LlamaForCausalLM`
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- **Number of Parameters**: ~3B
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- **Context Length**: 131,072
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## Quickstart
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### vLLM
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```bash
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pip install "vllm>=0.21"
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vllm serve ai9stars/G9v3-3B --port 8000
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```
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```bash
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curl http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "ai9stars/G9v3-3B",
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"messages": [{"role": "user", "content": "Who are you?"}],
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"max_tokens": 128,
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"temperature": 0.7
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}'
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```
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### SGLang
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```bash
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pip install "sglang[srt]>=0.5.12"
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python -m sglang.launch_server --model-path ai9stars/G9v3-3B --port 30000
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```
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```bash
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curl http://localhost:30000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "ai9stars/G9v3-3B",
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"messages": [{"role": "user", "content": "Who are you?"}],
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"max_tokens": 128,
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"temperature": 0.7
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}'
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```
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### Transformers
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```bash
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pip install -U "transformers>=5.6" accelerate torch
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```
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "ai9stars/G9v3-3B"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype="auto",
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device_map="auto",
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)
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messages = [{"role": "user", "content": "Who are you?"}]
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inputs = tokenizer.apply_chat_template(
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messages,
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tokenize=True,
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add_generation_prompt=True,
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enable_thinking=False,
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return_dict=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=128)
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print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))
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```
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Recommended sampling parameters:
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| Mode | Recommended params | Enable |
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| --- | --- | --- |
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| **Think** | `temperature=0.9, top_p=0.95` | `enable_thinking=True` |
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| **No Think** | `temperature=0.7, top_p=0.95` | `enable_thinking=False` |
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## Limitations and Responsible Use
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G9v3-3B is a language model that generates content based on learned statistical patterns from training data. It may produce inaccurate, biased, or unsafe outputs, and generated content should be reviewed and verified before use in high-stakes settings. Users are responsible for evaluating outputs, applying appropriate safeguards, and complying with applicable laws, regulations, and platform policies.
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## License
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This repository and the G9v3 model weights are released under the Apache-2.0 License.
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177
chat_template.jinja
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chat_template.jinja
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{{- bos_token }}{%- if tools %}
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{%- set tool_definitions %}
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{{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson(ensure_ascii=False) }}
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{%- endfor %}
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{{- '\n</tools>\n\nTool usage guidelines:\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\n- When calling a function, return an XML object within <function ... </function> using:\n<function name="function-name"><param name="param-name">param-value</param></function>\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name="param-name"><![CDATA[...multi-line value...]]></param>' }}
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{%- endset %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{%- if '<tool_def_sep>' in messages[0].content %}
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{{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
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{%- else %}
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{{- messages[0].content + '\n\n' + tool_definitions }}
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{%- endif %}
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{%- else %}
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{{- tool_definitions.lstrip() }}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- 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>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- set content_parts = content.split('<tool_sep>') %}
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{%- set processed_content = content_parts[0] %}
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{%- set tool_calls_count = message.tool_calls|length %}
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{%- set tool_sep_count = content_parts|length - 1 %}
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{%- set min_count = [tool_calls_count, tool_sep_count]|min %}
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|
||||
{%- for i in range(1, content_parts|length) %}
|
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{%- set tool_index = i - 1 %}
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{%- if tool_index < tool_calls_count %}
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{%- set tool_call = message.tool_calls[tool_index] %}
|
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{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{%- set single_tool_xml %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
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{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
||||
{{- param_value }}
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||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
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||||
{{- '</function>' }}
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||||
{%- endset %}
|
||||
{%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}
|
||||
{%- else %}
|
||||
{%- set processed_content = processed_content + content_parts[i] %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
|
||||
{%- if tool_calls_count > tool_sep_count %}
|
||||
{%- for remaining_index in range(tool_sep_count, tool_calls_count) %}
|
||||
{%- set tool_call = message.tool_calls[remaining_index] %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{%- set remaining_tool_xml %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
||||
{{- '<![CDATA[' + param_value + ']]>' }}
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||||
{%- else %}
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||||
{{- param_value }}
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||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- endset %}
|
||||
{%- set processed_content = processed_content + remaining_tool_xml %}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
|
||||
{%- set content = processed_content %}
|
||||
{%- endif %}
|
||||
|
||||
{%- if reasoning_content %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
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{%- elif '<think>' not in content and '</think>' not in content %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
|
||||
{%- if message.tool_calls and not has_tool_sep %}
|
||||
{%- 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 %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
||||
{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
||||
{{- param_value }}
|
||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- 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' }}
|
||||
{%- if message.content is string %}
|
||||
{{- content }}
|
||||
{%- else %}
|
||||
{{- message.content | tojson(ensure_ascii=False) }}
|
||||
{%- endif %}
|
||||
{{- '\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 %}
|
||||
{%- if enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- elif enable_thinking is true %}
|
||||
{{- '<think>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
30
config.json
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config.json
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|
||||
{
|
||||
"_name_or_path": "G9v3-3B",
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"bos_token_id": 0,
|
||||
"eos_token_id": [
|
||||
1,
|
||||
130073
|
||||
],
|
||||
"pad_token_id": 1,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 6144,
|
||||
"max_position_embeddings": 131072,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 52,
|
||||
"num_key_value_heads": 2,
|
||||
"head_dim": 128,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.57.1",
|
||||
"use_cache": true,
|
||||
"vocab_size": 130560,
|
||||
"rope_theta": 5000000.0
|
||||
}
|
||||
13
generation_config.json
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generation_config.json
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|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 0,
|
||||
"eos_token_id": [
|
||||
1,
|
||||
130073
|
||||
],
|
||||
"pad_token_id": 1,
|
||||
"do_sample": true,
|
||||
"temperature": 0.9,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "5.6.2"
|
||||
}
|
||||
3
model-00000-of-00002.safetensors
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3
model-00000-of-00002.safetensors
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
|
||||
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|
||||
size 5364538008
|
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model-00001-of-00002.safetensors
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3
model-00001-of-00002.safetensors
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||||
version https://git-lfs.github.com/spec/v1
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oid sha256:adeb387e7e2b74857e495ffb88a890f1db24c798fb04b4f805ca30ba3f1b9925
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||||
size 612829216
|
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478
model.safetensors.index.json
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478
model.safetensors.index.json
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@@ -0,0 +1,478 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 5977313280
|
||||
},
|
||||
"weight_map": {
|
||||
"model.embed_tokens.weight": "model-00000-of-00002.safetensors",
|
||||
"lm_head.weight": "model-00000-of-00002.safetensors",
|
||||
"model.layers.0.mlp.gate_proj.weight": "model-00000-of-00002.safetensors",
|
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"model.layers.0.mlp.up_proj.weight": "model-00000-of-00002.safetensors",
|
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"model.layers.1.mlp.gate_proj.weight": "model-00000-of-00002.safetensors",
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|
||||
}
|
||||
}
|
||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
653947
tokenizer.json
Normal file
653947
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
4099
tokenizer_config.json
Normal file
4099
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user