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Model: bytesbrains/naderu-geek-py-0.5b Source: Original Platform
2026-07-26 07:54:10 +08:00
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--- a/README.md
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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-0.5B-Instruct
+library_name: transformers
+pipeline_tag: text-generation
+language:
+  - en
+tags:
+  - code
+  - python
+  - coding-assistant
+  - lora
+  - naderu
+  - qwen2
+---
+
+# naderu-geek-py-0.5b
+
+**A small coding assistant by [Naderu](https://naderu.com) — a BytesBrains Pte. Ltd. venture.**
+
+`naderu-geek` is a compact, specialised coding model. It is a **portfolio / demonstration**
+piece: a LoRA fine-tune of an open coding base that gives the model a recognisable
+`naderu-geek` identity and a clean, commented Python style. It demonstrates Naderu's
+model-engineering pipeline — data → training → evaluation → release — end to end, on a
+deliberately small footprint.
+
+> **Status: released (v0.1.0).** Trained 2026-07-14 (LoRA fine-tune, merged) and passed its
+> qualitative smoke eval — see **Evaluation** below. Nothing here is a capability claim — see
+> **Limitations**.
+
+> This is an honest demonstration piece, **not** a state-of-the-art model. Its coding
+> ability is essentially that of its base; the fine-tune adds identity and style, not new
+> capability. See **Limitations**.
+
+## Provenance
+
+- **Fine-tuned from:** [`Qwen/Qwen2.5-Coder-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct) (Apache-2.0)
+- **Method:** LoRA (r=16, α=32; ~8.8M trainable params, 1.75%) on attention + MLP projections, adapter merged into the base
+- **Training data:** a small, Naderu-authored instruction set (39 examples: identity + idiomatic Python) — license-clean, included in our repo
+- **Precision:** trained in fp32; merged weights distributed in **bf16** (matching the base's format)
+- **License:** Apache-2.0 (inherits the base model's terms)
+
+## Intended use
+
+- A lightweight Python coding helper: small functions, snippets, explanations.
+- A reference example of a Naderu specialised-model release (card + provenance + eval).
+
+**Out of scope:** production code generation at scale, non-Python languages, security-
+sensitive code, or any use where correctness must be guaranteed without review.
+
+## How to use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "bytesbrains/naderu-geek-py-0.5b"
+tok = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+messages = [
+    {"role": "system", "content": "You are naderu-geek, a focused coding assistant by Naderu (naderu.com). You write clean, correct, well-commented code and explain briefly."},
+    {"role": "user", "content": "Write a Python function to check if a number is prime."},
+]
+enc = tok.apply_chat_template(
+    messages, add_generation_prompt=True, return_tensors="pt", return_dict=True
+)
+out = model.generate(**enc, max_new_tokens=200, do_sample=False)
+print(tok.decode(out[0, enc["input_ids"].shape[1]:], skip_special_tokens=True))
+```
+
+The model is chat-templated (Qwen2 template). The system prompt above is the one it was
+trained with; keeping it yields the most on-style responses.
+
+## Evaluation
+
+<!-- EVAL:START -->
+**Suite:** `eval/suites/naderu-geek/run_eval.py` (qualitative smoke, greedy decode) ·
+**Run:** 2026-07-14 · **Result: PASS**
+
+| Check | Outcome |
+|-------|---------|
+| Identity recognised (`Who are you?` → names `naderu-geek`) | ✅ yes |
+| Coherent, runnable Python (3 in-suite coding prompts) | ✅ 3/3 |
+
+Observations (honest):
+
+- **Identity imprinted and robust.** It reliably self-identifies as `naderu-geek` by Naderu,
+  and on a held-out prompt (*"Are you ChatGPT or made by OpenAI?"*) it correctly denies and
+  states its open-base provenance — i.e. the identity generalises beyond the exact training phrasings.
+- **Clean Python style generalises.** On held-out tasks not in the training set (mean of a list,
+  nth triangular number) it produced correct, type-hinted, docstring'd functions in the same
+  house style — so the fine-tune transfers *style*, not just memorised answers.
+- **In line with the base's capability.** In-suite answers closely track the curated exemplars
+  (a 39-example set, low final train loss). This is the expected behaviour of a small identity/
+  style imprint and **not** a capability claim — see **Limitations**.
+
+Reproduce: `python training/train_lora.py && NG_MODEL=./naderu-geek-py-0.5b python eval/suites/naderu-geek/run_eval.py`
+<!-- EVAL:END -->
+
+This is a qualitative smoke check (identity recognised + coherent Python), not a
+leaderboard score. For real releases, Naderu attaches reproducible benchmark results
+tied to a versioned eval suite.
+
+## Limitations & risks
+
+- Tiny base (0.5B) + tiny fine-tune → limited reasoning; can produce incorrect or
+  insecure code. **Always review generated code.**
+- The fine-tune changes identity/style far more than capability.
+- English + Python focus; other languages are best-effort from the base.
+
+## About Naderu
+
+[**Naderu**](https://naderu.com) is an AI-models company — a venture of **BytesBrains Pte. Ltd.**
+We do three things, and only these:
+
+- **Train** — turn foundation models into specialised ones (fine-tune, LoRA, distill, quantize).
+- **Release** — publish specialised models with model cards, provenance, and clear licensing.
+- **Serve** — the engineering around models (customization, deployment, operations).
+
+Every Naderu model states its upstream foundation model and licence plainly, and every capability
+claim is backed by a real evaluation — never vibes. `naderu-geek-py-0.5b` is our **first public
+portfolio release**: small on purpose, honest about its scope, and reproducible end to end.
+
+## Links
+
+- 🌐 Website — [naderu.com](https://naderu.com)
+- 🧩 Model family — `naderu-geek` (compact, specialised coding models)
+- 🧱 Base model — [`Qwen/Qwen2.5-Coder-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct)
+- 🪪 License — [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
+- 🏷️ Version — v0.1.0 (released 2026-07-14)
+
+## Citation / attribution
+
+Built on Qwen2.5-Coder (Apache-2.0). Fine-tuned and released by **Naderu** (BytesBrains Pte. Ltd.).
+
+```bibtex
+@misc{naderu_geek_py_0_5b_2026,
+  title        = {naderu-geek-py-0.5b},
+  author       = {Naderu (BytesBrains Pte. Ltd.)},
+  year         = {2026},
+  howpublished = {\url{https://huggingface.co/bytesbrains/naderu-geek-py-0.5b}},
+  note         = {LoRA fine-tune of Qwen/Qwen2.5-Coder-0.5B-Instruct, Apache-2.0}
+}
+```
--- a/chat_template.jinja
+++ b/chat_template.jinja
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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\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' }}
+{%- endif %}
--- a/config.json
+++ b/config.json
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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 896,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 24,
+  "model_type": "qwen2",
+  "num_attention_heads": 14,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.13.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
--- a/generation_config.json
+++ b/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": "5.13.1"
+}
--- a/model.safetensors
+++ b/model.safetensors
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+size 988097824
--- a/tokenizer.json
+++ b/tokenizer.json
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+oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
+size 11421892
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
@@ -0,0 +1,30 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 32768,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}