| --- |
| base_model: Qwen/Qwen3-1.7B |
| base_model_relation: adapter |
| library_name: peft |
| pipeline_tag: text-generation |
| inference: false |
| language: |
| - en |
| license: other |
| license_name: 0bsd |
| license_link: https://github.com/codegeist-ai/codegeist-ai/blob/main/LICENSE |
| tags: |
| - peft |
| - lora |
| - sft |
| - transformers |
| - unsloth |
| - non-production |
| - identity-smoke |
| --- |
| |
| # Codegeist Qwen3-1.7B Identity Smoke Adapter |
|
|
| This is a non-production LoRA adapter created to validate the Codegeist training |
| pipeline. It teaches one response only: |
|
|
| ```text |
| User: What is Codegeist? |
| Assistant: Codegeist is a coding agent. |
| ``` |
|
|
| It is not evidence of coding ability, reasoning, generalization, safe tool use, |
| Codegeist OS integration, GGUF conversion, Vulkan deployment, or production |
| model quality. |
|
|
| ## Artifact Identity |
|
|
| | Field | Value | |
| | --- | --- | |
| | Base model | `Qwen/Qwen3-1.7B` | |
| | Base revision | `70d244cc86ccca08cf5af4e1e306ecf908b1ad5e` | |
| | Adapter format | PEFT LoRA, Safetensors | |
| | Adapter weight SHA-256 | `19d424106ef88ffeac4c26c22cebfb13ae1d5f309e1dcccf2da708727bec10a8` | |
| | Training Job | `6a75f25a3e1f34a7e32bd646` | |
| | Training date | 2026-08-07 | |
|
|
| `evidence.json` contains the sanitized run chronology, configuration, package |
| versions, hashes, cost estimate, verification status, and known gaps. It does |
| not contain model weights, private logs, or credentials. |
|
|
| ## Intended Use |
|
|
| The only intended use is reproducing and inspecting this one-record pipeline |
| smoke. Use the immutable base revision above and pin this adapter repository to |
| a specific Hub commit when loading it. |
|
|
| Do not use this adapter as a coding assistant, autonomous agent, general chat |
| model, safety component, or production model. It was not evaluated for those |
| purposes. |
|
|
| ## Loading |
|
|
| This CPU-compatible example prioritizes portability over speed. Replace |
| `ADAPTER_REVISION` with an immutable commit from this repository: |
|
|
| ```python |
| import torch |
| from peft import PeftModel |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| BASE_MODEL = "Qwen/Qwen3-1.7B" |
| BASE_REVISION = "70d244cc86ccca08cf5af4e1e306ecf908b1ad5e" |
| ADAPTER_MODEL = "codegeist/qwen3-1.7b-codegeist-identity-smoke" |
| ADAPTER_REVISION = "04d51edac56c6f1e068c644bfa8d014cadcecf9f" |
| |
| tokenizer = AutoTokenizer.from_pretrained( |
| BASE_MODEL, |
| revision=BASE_REVISION, |
| trust_remote_code=False, |
| ) |
| base_model = AutoModelForCausalLM.from_pretrained( |
| BASE_MODEL, |
| revision=BASE_REVISION, |
| trust_remote_code=False, |
| torch_dtype=torch.float32, |
| low_cpu_mem_usage=True, |
| ) |
| model = PeftModel.from_pretrained( |
| base_model, |
| ADAPTER_MODEL, |
| revision=ADAPTER_REVISION, |
| is_trainable=False, |
| ) |
| |
| prompt = tokenizer.apply_chat_template( |
| [{"role": "user", "content": "What is Codegeist?"}], |
| tokenize=False, |
| add_generation_prompt=True, |
| enable_thinking=False, |
| ) |
| inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False) |
| with torch.inference_mode(): |
| output = model.generate( |
| **inputs, |
| do_sample=False, |
| temperature=None, |
| top_p=None, |
| top_k=None, |
| max_new_tokens=64, |
| pad_token_id=tokenizer.eos_token_id, |
| eos_token_id=tokenizer.eos_token_id, |
| ) |
| |
| response = tokenizer.decode( |
| output[0, inputs["input_ids"].shape[1]:], |
| skip_special_tokens=True, |
| ).strip() |
| print(response) |
| ``` |
|
|
| Expected whitespace-normalized response: |
|
|
| ```text |
| Codegeist is a coding agent. |
| ``` |
|
|
| ## Training Data |
|
|
| The complete project-authored synthetic dataset is one public record: |
|
|
| ```json |
| { |
| "instruction": "What is Codegeist?", |
| "response": "Codegeist is a coding agent." |
| } |
| ``` |
|
|
| The record ID is `codegeist-identity-v1-001`. It contains no private data, |
| personal information, or credentials. Training and evaluation deliberately use |
| the same record to test memorization; there is no held-out evaluation set. |
|
|
| ## Training |
|
|
| - Python 3.12 |
| - PyTorch 2.6.0 with CUDA 12.4 |
| - Unsloth 2026.8.7 |
| - Transformers 5.5.0 |
| - TRL 0.24.0 |
| - PEFT 0.20.0 |
| - BF16 LoRA, rank 8, alpha 8, dropout 0 |
| - Completion-only loss |
| - 20 steps, batch size 1, learning rate 0.0002 |
| - Seed and data seed 3407 |
| - NVIDIA A10G |
| - No intermediate checkpoints and no automatic Hub publication |
|
|
| The aggregate training loss was `1.6867698234826094`. The final logged step loss |
| was approximately `0.0003`. |
|
|
| ## Evaluation |
|
|
| The unchanged base model incorrectly described Codegeist as a code editor. After |
| training, the adapter was loaded onto a fresh instance of the exact base revision |
| in a child process. One greedy generation produced the expected answer after |
| leading and trailing whitespace normalization. |
|
|
| The raw decoded continuation before `.strip()` was not retained. Training and |
| inference repeatability, deterministic PyTorch algorithms, coding benchmarks, |
| safety evaluation, and generalization were not tested. |
|
|
| Before public release, an independent local CPU reload used PyTorch 2.6.0+cpu, |
| Transformers 5.5.0, PEFT 0.20.0, the immutable base revision, and adapter commit |
| `04d51edac56c6f1e068c644bfa8d014cadcecf9f`. In that publication test, both the |
| raw and whitespace-normalized responses were exactly |
| `Codegeist is a coding agent.`. This confirms public-artifact loading and the |
| single memorized response only; it does not broaden the interpretation boundary. |
|
|
| ## Licenses And Provenance |
|
|
| The project-authored adapter and documentation are provided under the |
| [BSD Zero Clause License](https://github.com/codegeist-ai/codegeist-ai/blob/main/LICENSE). |
| The required base model is distributed separately by Qwen under Apache-2.0. This |
| repository does not redistribute base-model weights. Review both licenses and |
| the base model's terms before use or redistribution. |
|
|
| See `THIRD_PARTY_NOTICES.md` for the exact upstream model reference. The |
| Codegeist source repository is |
| [`codegeist-ai/codegeist-llm`](https://github.com/codegeist-ai/codegeist-llm). |
|
|
| ## Publication Limitations |
|
|
| - The successful training source was not committed when the paid Job launched; |
| exact source bytes are anchored by SHA-256 in `evidence.json`. |
| - Downloaded model and tokenizer cache bytes were not independently rehashed |
| inside the Job against the upstream manifest. |
| - The generated adapter configuration originally omitted the base revision; the |
| publication copy sets it to the immutable revision used by the Job. |
| - This publication does not change the experiment's non-production status. |
|
|
