初始化项目，由ModelHub XC社区提供模型

Model: WithinUsAI/Gemini3.5-Code.Reasoner-2b-Distilled
Source: Original Platform

.gitattributes

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz 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

README.md

@@ -0,0 +1,84 @@
+---
+license: apache-2.0
+tags:
+- text-generation
+- code
+- reasoning
+- codegemma
+- gemma
+- safe-tensors
+- distillation
+- synthetic-dataset
+base_model: google/codegemma-1.1-2b
+datasets:
+- WithinUsAI/GeminiPro3.2_max_distill_god_seed_25k
+- WithinUsAI/gemini_3.5_flash_distilled_25k
+- WithinUsAI/Gemini_3.2_Pro_Distilled
+- WithinUsAI/codegemma_gemini_pro_32_distilled_25k
+- WithinUsAI/DEEPMIND_Alpha_Distilled
+pipeline_tag: text-generation
+library_name: transformers
+language:
+- en
+---
+
+# Gemini3.5-Code.Reasoner-2b-Distilled
+
+Gemini3.5-Code.Reasoner-2b-Distilled is a highly efficient, reasoning-dense model tailored for advanced coding tasks, algorithmic problem-solving, and logical chain-of-thought workflows. 
+
+By applying a specialized Low-Rank Adaptation (LoRA) layer over **CodeGemma 1.1 2B**, this model infuses frontier-level reasoning mechanics into a compact, 2-billion parameter architecture. It bridges the gap between massive cloud-hosted models and local, edge-compute hardware.
+
+## Model Details
+
+- **Developed by:** WithinUsAI
+- **Model Type:** Causal Language Model (Fine-tuned / Knowledge Distilled)
+- **Base Model:** [google/codegemma-1.1-2b](https://huggingface.co/google/codegemma-1.1-2b)
+- **Architecture:** GemmaForCausalLM (CodeGemma variant) + LoRA Adapters
+- **License:** Apache 2.0
+
+## Training & Dataset Recipe
+
+The "Reasoner" capabilities of this model are distilled from a multi-source synthetic pipeline focusing on complex coding logic, algorithmic optimization, and step-by-step thinking patterns. The training mixture leverages approximately 100K+ high-quality reasoning examples across five core datasets:
+
+| Dataset Name | Source / Focus | Approx. Size |
+| :--- | :--- | :--- |
+| `WithinUsAI/GeminiPro3.2_max_distill_god_seed_25k` | High-quality frontier seed prompts for code generation. | ~25k samples |
+| `WithinUsAI/gemini_3.5_flash_distilled_25k` | Fast, iterative logical steps and multi-turn debugging data. | ~25k samples |
+| `WithinUsAI/Gemini_3.2_Pro_Distilled` | Heavy math logic, structural coding, and system design patterns. | Premium corpus |
+| `WithinUsAI/codegemma_gemini_pro_32_distilled_25k` | Target-aligned distillation data optimized for the CodeGemma vocabulary. | ~25k samples |
+| `WithinUsAI/DEEPMIND_Alpha_Distilled` | Deep algorithmic competitive programming and math reasoning. | Premium corpus |
+
+## Intended Use
+
+- **Local Code Assistants:** Ideal for IDE plugins requiring fast, low-latency code completion and instruction following.
+- **Logical Chain-of-Thought:** Designed to output its reasoning process before writing the final code block, minimizing syntax and logical errors.
+- **Resource-Constrained Environments:** Can easily be deployed on mobile devices, single-GPU setups, or local laptops using frameworks like `vLLM`, `Ollama`, or `SGLang`.
+
+## Quickstart Guide
+
+### Inference with Hugging Face Transformers
+
+Because CodeGemma utilizes specialized tokens for coding workflows, it's recommended to structure your prompts cleanly to prompt the model's inner chain-of-thought.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "WithinUsAI/Gemini3.5-Code.Reasoner-2b-Distilled"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+
+# Prompt the model to think step-by-step before delivering code
+prompt = """<bos>Analyze the problem and think step-by-step before writing any code.
+Problem: Write a Python generator function that yields the Fibonacci sequence up to n elements.
+Answer:"""
+
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.2)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))

config.json

@@ -0,0 +1,32 @@
+{
+  "architectures": [
+    "GemmaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
+  "dtype": "float16",
+  "eos_token_id": 1,
+  "head_dim": 256,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_activation": null,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 16384,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 18,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_bidirectional_attention": null,
+  "use_cache": true,
+  "vocab_size": 256000
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "5.0.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:782d4cc509fce11347b1943f8270e4d6d6fb19ad715159eef10fd4aded600238
+size 5012363688

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:88649feb2ca8710ba0b8d7402ac0dc737b2b4cc58f4a10878127449a01cee96c
+size 34362790

tokenizer_config.json

@@ -0,0 +1,15 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<bos>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "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
+}