Duplicate from GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking

Co-authored-by: LOL <GnLOLot@users.noreply.huggingface.co>

.gitattributes

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README-cn.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+  - en
+  - zh
+base_model: openbmb/MiniCPM5-1B
+base_model_relation: finetune
+pipeline_tag: text-generation
+tags:
+  - minicpm
+  - minicpm5
+  - thinking
+  - fable5
+  - coding
+  - instruction-following
+---
+
+<p align="center">
+  <img src="assets/banner.png" alt="MiniCPM5-1B-Claude-Opus-Fable5-Thinking" width="100%"/>
+</p>
+
+# MiniCPM5-1B-Claude-Opus-Fable5-Thinking
+
+> **📢 V2.0 已发布** — 我们已发布增强 **工具调用** 能力的新版本，欢迎通过以下链接下载体验：
+> - Transformers：[MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking)
+> - GGUF：[MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF)
+
+GGUF 量化版：**[MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF)**
+
+[English README](./README.md)
+
+**MiniCPM5-1B-Claude-Opus-Fable5-Thinking** 是基于 [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B) 的 1B **Thinking** 语言模型。该模型使用 **Fable 5** 数据进一步微调，增强了 **Coding（编程）** 与 **指令遵循（Instruction Following）** 能力，同时保留 MiniCPM5 原生的 Thinking 对话模板与工具调用格式。
+
+llama.cpp / Ollama / LM Studio 部署请参阅 **[GGUF 仓库](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF)**。
+
+---
+
+## 模型概述
+
+| 项目 | 说明 |
+|---|---|
+| **基座模型** | [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)（1B 稠密 Llama 架构） |
+| **后训练数据** | Fable 5 traces |
+| **主要提升** | 相较基座，Coding 与指令遵循能力更强 |
+| **对话格式** | MiniCPM5 原生 Thinking 模板，支持可选的思维链推理块 |
+| **上下文长度** | **128K**（`max_position_embeddings = 131072`） |
+| **部署特点** | 单卡友好，适合边缘 / 本地场景 |
+
+---
+
+## 能力
+
+- **Coding** — 代码生成、调试及软件工程类任务
+- **Instruction Following** — 更稳定地遵循用户提示与结构化任务约束
+- **Thinking 模式** — 通过 MiniCPM5 对话模板进行思维链推理
+- **工具调用** — 继承 MiniCPM5 的 XML 工具调用格式
+- **长上下文** — 最高 **128K tokens**（`config.json` 中为 131,072）
+
+---
+
+## 快速开始
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, trust_remote_code=True,
+    torch_dtype=torch.bfloat16, device_map="auto",
+)
+
+messages = [{"role": "user", "content": "写一个 Python 函数，合并两个有序链表。"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, do_sample=False)
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+---
+
+## 采样建议
+
+生成参数继承自 **[MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)**：
+
+| 模式 | 参数 |
+|---|---|
+| **Think**（默认） | `temperature=0.9, top_p=0.95` |
+| **No Think** | `temperature=0.7, top_p=0.95`，`enable_thinking=False` |
+
+---
+
+## 局限性
+
+- **Thinking 输出** — 模型可能在最终回答前输出推理块；下游应用可在展示前将其剥离
+- **1B 体量** — 面向轻量本地部署，非前沿规模通用推理模型
+
+---
+
+## 许可与致谢
+
+- 许可证：**Apache-2.0**（继承自 MiniCPM5-1B）
+- 基座：[OpenBMB / MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)
+- GGUF：[llama.cpp](https://github.com/ggml-org/llama.cpp)

README.md

@@ -0,0 +1,114 @@
+---
+library_name: transformers
+license: apache-2.0
+language:
+  - en
+  - zh
+base_model: openbmb/MiniCPM5-1B
+base_model_relation: finetune
+pipeline_tag: text-generation
+tags:
+  - minicpm
+  - minicpm5
+  - llama
+  - text-generation
+  - thinking
+  - fable5
+  - coding
+  - instruction-following
+---
+
+<p align="center">
+  <img src="assets/banner.png" alt="MiniCPM5-1B-Claude-Opus-Fable5-Thinking" width="100%"/>
+</p>
+
+# MiniCPM5-1B-Claude-Opus-Fable5-Thinking
+
+> **📢 V2.0 is available** — We have released an updated model with **enhanced tool-calling** capabilities. Welcome to try the new version:
+> - Transformers: [MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking)
+> - GGUF: [MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF)
+
+GGUF quantizations for local deployment: **[MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF)**
+
+[中文说明](./README-cn.md)
+
+**MiniCPM5-1B-Claude-Opus-Fable5-Thinking** is a compact 1B **Thinking** language model built on [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B). It is further fine-tuned on **Fable 5** data to improve **coding** and **instruction-following** while keeping MiniCPM5's native Thinking chat template and tool-call format.
+
+For llama.cpp / Ollama / LM Studio deployment, see the **[GGUF repository](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF)**.
+
+---
+
+## Overview
+
+| Item | Detail |
+|---|---|
+| **Base model** | [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B) (1B dense Llama architecture) |
+| **Post-training** | Fable 5 traces |
+| **Key gains** | Stronger coding and instruction following vs. the base checkpoint |
+| **Chat format** | MiniCPM5 native Thinking template with optional chain-of-thought blocks |
+| **Context length** | **128K** (`max_position_embeddings = 131072`) |
+| **Deployment** | Single-GPU friendly; suitable for edge / local use |
+
+---
+
+## Capabilities
+
+- **Coding** — code generation, debugging, and software-engineering-style tasks
+- **Instruction following** — more reliable adherence to user prompts and structured constraints
+- **Thinking mode** — chain-of-thought reasoning via the MiniCPM5 chat template
+- **Tool calling** — inherits MiniCPM5's XML tool-call format
+- **Long context** — up to **128K tokens** (131,072 tokens per `config.json`)
+
+---
+
+## Quick start
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [{"role": "user", "content": "Write a Python function to merge two sorted lists."}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, do_sample=False)
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+---
+
+## Sampling recommendations
+
+Generation defaults are inherited from **[MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)**:
+
+| Mode | Params |
+|---|---|
+| **Think** (default) | `temperature=0.9, top_p=0.95` |
+| **No Think** | `temperature=0.7, top_p=0.95`, `enable_thinking=False` |
+
+---
+
+## Limitations
+
+- **Thinking outputs** — the model may emit reasoning blocks before the final answer; downstream apps can strip them before display
+- **1B scale** — optimized for lightweight local deployment, not frontier-scale general reasoning
+
+---
+
+## Provenance & licensing
+
+Released under **Apache-2.0**, inherited from [MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B).
+
+## Acknowledgements
+
+- Base model: [OpenBMB / MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)
+- GGUF conversion: [llama.cpp](https://github.com/ggml-org/llama.cpp)

chat_template.jinja

@@ -0,0 +1,179 @@
+{{- bos_token }}{%- if tools %}
+    {%- set tool_definitions %}
+        {{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+        {%- for tool in tools %}
+            {{- "\n" }}
+            {{- tool | tojson(ensure_ascii=False) }}
+        {%- endfor %}
+        {{- '\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>' }}
+    {%- endset %}
+    
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {%- if '<tool_def_sep>' in messages[0].content %}
+            {{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
+        {%- else %}
+            {{- messages[0].content + '\n\n' + tool_definitions }}
+        {%- endif %}
+    {%- else %}
+        {{- tool_definitions.lstrip() }}
+    {%- endif %}
+    {{- '<|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 message.tool_calls %}
+            {%- set content_parts = content.split('<tool_sep>') %}
+            {%- set processed_content = content_parts[0] %}
+            {%- set tool_calls_count = message.tool_calls|length %}
+            {%- set tool_sep_count = content_parts|length - 1 %}
+            {%- set min_count = [tool_calls_count, tool_sep_count]|min %}
+            
+            {%- for i in range(1, content_parts|length) %}
+                {%- set tool_index = i - 1 %}
+                {%- if tool_index < tool_calls_count %}
+                    {%- set tool_call = message.tool_calls[tool_index] %}
+                    {%- 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) %}
+                                    {{- '<![CDATA[' + param_value + ']]>' }}
+                                {%- else %}
+                                    {{- param_value }}
+                                {%- endif %}
+                                {{- '</param>' }}
+                            {%- endfor %}
+                        {%- endif %}
+                        {{- '</function>' }}
+                    {%- 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 + ']]>' }}
+                                {%- else %}
+                                    {{- param_value }}
+                                {%- endif %}
+                                {{- '</param>' }}
+                            {%- endfor %}
+                        {%- endif %}
+                        {{- '</function>' }}
+                    {%- endset %}
+                    {%- set processed_content = processed_content + remaining_tool_xml %}
+                {%- endfor %}
+            {%- endif %}
+            
+            {%- set content = processed_content %}
+        {%- endif %}
+        
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if 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 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 %}

config.json

@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "bfloat16",
+  "eos_token_id": [
+    1,
+    130073
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 4608,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "pad_token_id": 1,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 5000000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.6.0",
+  "use_cache": true,
+  "vocab_size": 130560
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    130073
+  ],
+  "pad_token_id": 1,
+  "temperature": 0.9,
+  "top_p": 0.95,
+  "transformers_version": "5.6.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:689e9f7eb54a22c91b02e57bb2af884693184db963845cffcae373df47f9b178
+size 2161290944

tokenizer_config.json

@@ -0,0 +1,22 @@
+{
+  "add_prefix_space": null,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": [
+    "<|im_end|>"
+  ],
+  "is_local": true,
+  "legacy": true,
+  "local_files_only": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "split_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}