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Model: eivintobias/heartly-qwen-code
Source: Original Platform

README.md

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+---
+language:
+  - en
+license: mit
+base_model: Qwen/Qwen2.5-Coder-1.5B
+library_name: transformers
+model_type: qwen2
+tags:
+  - code
+  - hallucination-reduction
+  - heartly
+  - decide-verify-stop
+  - boundary-head
+  - pytorch
+  - text-generation
+---
+
+# Heartly Qwen-Code v3
+
+A 1.5B coding LLM with the **Heartly** hallucination-reduction architecture,
+fine-tuned from **Qwen2.5-Coder-1.5B** with the conversational Stage-5 SFT recipe
+(Fix1–4: natural phrasing, single refusal, persona — 5,200 samples in
+`heartly-qwen-code/sft_dataset_code_v3.jsonl`).
+
+v3 builds on the same v1/v2 Stage 1–4 numbers (grammar adoption 100%, boundary-head
+AUROC 1.000, critic AUROC 1.000) — same Qwen2.5-Coder-1.5B base, now trained for
+multi-turn conversational code chat. See [`HF_MODEL_CARD.md`](HF_MODEL_CARD.md) for
+the Stage 1–2 probe/critic results carried over from the identical architecture.
+
+## Output grammar
+
+```
+ thinking [reasoning]  response<decide>speak|stop</decide><verify>known|unknown</verify> [answer] <stop>
+```
+
+Only `[answer]` should reach the user.
+
+## Usage
+
+### 0. Recommended — chat via the GitHub server (strips the grammar for you)
+
+This model emits the Heartly grammar as ordinary multi-token text (the tags are
+**not** tokenizer special tokens), so some front-ends (e.g. LM Studio) may decode
+them mangled. The **`server.py`** FastAPI loader on GitHub loads this model and
+runs every reply through **`reply_formatter.py`**, which canonicalises the tags
+and returns only the clean answer.
+
+```bash
+pip install -r requirements.txt   # fastapi + uvicorn + transformers + torch
+python server.py --model eivintobias/heartly-qwen-code --port 8000
+
+curl -X POST http://127.0.0.1:8000/chat \
+  -H "Content-Type: application/json" \
+  -d '{"prompt":"Write a function that reverses a string"}'
+```
+
+Response: `{"model":"eivintobias/heartly-qwen-code","raw":"...<decide>...","reply":"<clean answer>"}`.
+
+Quick browser test (no curl): open `http://127.0.0.1:8000/` — `server.py` serves an
+HTML chat UI at `GET /`. The first message lazy-loads the model; code answers render
+with real line breaks, and the Heartly grammar is stripped by the reply formatter.
+
+Quick offline test (no server): `python chat_smoke.py "Write a function that sorts a list"`.
+
+📦 **Model card source:** this file (`HF_MODEL_CARD_v3.md`). When uploaded to
+HuggingFace, copy it to `README.md` on the hub repo.
+
+### 1. Transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+tok = AutoTokenizer.from_pretrained("eivintobias/heartly-qwen-code")
+model = AutoModelForCausalLM.from_pretrained(
+    "eivintobias/heartly-qwen-code", torch_dtype=torch.float32, device_map="cpu"
+)
+model.eval()
+ids = tok.encode("User: Write a function that reverses a string\nAssistant: ", return_tensors="pt")
+out = model.generate(**ids, max_new_tokens=256, pad_token_id=tok.eos_token_id, do_sample=False)
+raw = tok.decode(out[0][ids.shape[1]:], skip_special_tokens=False)
+# Strip the grammar -> clean answer:
+from reply_formatter import format_reply
+print(format_reply(raw))
+```
+
+> `reply_formatter.py` (grammar strip) and `server.py` are bundled in this repo (HF clone = flat layout; GitHub = `heartly-qwen-code/`). Clone it so `from reply_formatter import format_reply` resolves before the offline example.
+
+## Files in this repo
+
+| File | Description |
+|------|-------------|
+| `config.json` | Qwen2ForCausalLM (28 layers, d=1536) + `heartly_stop_token_id=9495` |
+| `generation_config.json` | default generate params |
+| `chat_template.jinja` | standard Qwen chat template |
+| `tokenizer.json` / `tokenizer_config.json` | Qwen BPE tokenizer |
+| `model.safetensors` | v3 fine-tuned weights (**full fine-tune**, not a LoRA adapter) |
+| `server.py` | FastAPI server: lazy-loads the model; serves `/`, `/health`, `/chat`; strips Heartly grammar via reply_formatter |
+| `reply_formatter.py` | strips `thinking` / `<decide>` / `<verify>` / `<stop>` -> clean answer; unescapes code newlines |
+| `chat_smoke.py` | offline load + chat smoke test (no server) |
+| `requirements.txt` | torch, transformers, fastapi, uvicorn, sentencepiece, datasets, scikit-learn, numpy, accelerate, huggingface_hub |
+
+## Training
+
+- **Base:** Qwen/Qwen2.5-Coder-1.5B
+- **Method:** full fine-tune (fp16), max-length 512, 2 epochs, freeze bottom 12 layers
+- **Dataset:** `sft_dataset_code_v3.jsonl` (5,200 conversational Heartly samples)
+- **GPU:** 1× RTX 3090 (24GB)
+
+## License
+
+MIT — built on Qwen2.5-Coder (Apache 2.0).
+
+## Links
+
+- [GitHub (server + tools)](https://github.com/eivintobias/heartly/tree/master/heartly-qwen-code)
+- [v1/v2 model card (LoRA)](HF_MODEL_CARD.md)
+- [Heartly RWKV7 model](https://huggingface.co/eivintobias/heartly-rwkv7-1.5b)