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Model: opensynapselabs/arche3.5-codium-0.5B
Source: Original Platform

.gitattributes

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README.md

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+---
+tags:
+- code
+- code-generation
+- code-completion
+- code-llm
+- python
+- programming
+- developer-tools
+- instruct
+- finetuned
+- qwen
+- small-model
+- edge-device
+- local-ai
+- open-source
+- humaneval
+- function-calling
+- cli-tool
+- arche-code
+- text-generation
+- causal-lm
+- transformers
+- lightweight
+- cpu-friendly
+- apple-silicon
+- inference
+- autocomplete
+- llm
+- 500m
+- python-code
+license: apache-2.0
+language:
+- en
+- code
+spaces:
+- opensynapselabs/arche-codium-playground
+base_model:
+- Qwen/Qwen2.5-0.5B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+---
+# Arche-Codium-500M
+
+Compact, instruction-finetuned code generation model built on **Qwen2.5-Coder-0.5B-Instruct**. Fast local code completion with minimal resources.
+
+## TL;DR
+
+- **500M parameters** — runs on CPU, MPS, or low-VRAM GPU
+- **80% pass rate** on HumanEval (16/20 tasks)
+- **Apache 2.0** — fully open, commercially usable
+- **CLI-ready** — plug into [arche-code](https://github.com/OpenSynapseLabs/arche-code)
+
+## Live Demo
+
+Try the model directly in your browser — no setup required:
+
+[![Open in Spaces](https://huggingface.co/datasets/huggingface/badges/resolve/main/open-in-hf-spaces-md.svg)](https://huggingface.co/spaces/opensynapselabs/arche-codium-playground)
+
+## Quick Start
+
+### With arche-code CLI
+
+```bash
+git clone https://github.com/OpenSynapseLabs/arche-code.git
+cd arche-code
+pip install -e .
+arche --provider arche --model arche-codium-500m write "def fibonacci(n):" --max-tokens 256
+```
+
+The CLI auto-downloads the model on first use. Full docs: [github.com/OpenSynapseLabs/arche-code](https://github.com/OpenSynapseLabs/arche-code)
+
+### With transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "OpenSynapseLabs/arche-codium-500m",
+    torch_dtype="auto", device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("OpenSynapseLabs/arche-codium-500m")
+
+prompt = '''def has_close_elements(numbers: list[float], threshold: float) -> bool:
+    """Check if any two numbers are closer than threshold."""'''
+
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=128, temperature=0.2)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Benchmarks
+
+| Benchmark | Result |
+|-----------|--------|
+| **HumanEval** | **16/20 (80%)** |
+
+## What This Model Is
+
+- **Lead magnet** — free, capable entry point into the Arche ecosystem
+- **Edge-friendly** — runs on laptops, Raspberry Pi, mobile devices
+- **Real code** — generates executable Python, not just snippets
+
+## What This Model Is Not
+
+- A replacement for 7B+ models on complex architecture tasks
+- A chat model — instruction-tuned for code generation only
+- The final word — larger Arche coding models are shipping this month
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Base model | Qwen2.5-Coder-0.5B-Instruct |
+| Parameters | 0.49B |
+| License | Apache 2.0 |
+| Training | Instruction fine-tuning on code-completion tasks |
+
+## Hardware Requirements
+
+| Device | VRAM/RAM | Speed |
+|--------|----------|-------|
+| Apple Silicon (MPS) | 2 GB unified | ~50 tok/s |
+| NVIDIA GPU (CUDA) | 2 GB | ~80 tok/s |
+| CPU only | 4 GB RAM | ~10 tok/s |
+
+## Limitations
+
+- Struggles with multi-step reasoning (e.g., LRU cache with TTL)
+- May truncate output at `max_tokens` limits — increase if code cuts off
+- Hallucinates imports occasionally — always verify generated code
+- Best for functions under 50 lines; breaks down on large classes
+
+## Citation
+
+```bibtex
+@software{arche_codium_500m,
+  author = {Open Synapse Labs},
+  title = {Arche-Codium-500M: Compact Code Generation Model},
+  year = {2026},
+  url = {https://huggingface.co/OpenSynapseLabs/arche-codium-500m}
+}
+```
+
+## Contact
+
+📧 opensynapselabs@proton.me  
+🐙 [github.com/OpenSynapseLabs](https://github.com/OpenSynapseLabs)
+
+---
+
+*Built by Open Synapse Labs. Base model: Qwen2.5-Coder-0.5B-Instruct (Apache 2.0).*

added_tokens.json

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+{
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+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
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+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
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+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-Coder-0.5B-Instruct",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 896,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 24,
+  "model_type": "qwen2",
+  "num_attention_heads": 14,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.44.2"
+}

model.safetensors

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+oid sha256:a4d4855fd547bf29059e84fbd641d32c596bf7047e99053580e43520e656e987
+size 988097536

special_tokens_map.json

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+{
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
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+    "lstrip": false,
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+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
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+    "<|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    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\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    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.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{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "max_length": 768,
+  "model_max_length": 32768,
+  "pad_token": "<|im_end|>",
+  "split_special_tokens": false,
+  "stride": 0,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": null
+}