Publish experimental Codegeist Q4_K_M GGUF

Add the complete merged Docker Model Runner interoperability artifact and its reviewed provenance metadata.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* 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
+gguf/codegeist-llm-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,214 +1,66 @@
 ---
 base_model: Qwen/Qwen3-1.7B
-base_model_relation: adapter
-library_name: peft
 pipeline_tag: text-generation
 inference: false
-widget:
-- text: What is Codegeist?
 language:
 - en
 license: other
-license_name: 0bsd
-license_link: https://github.com/codegeist-ai/codegeist-ai/blob/main/LICENSE
+license_name: apache-2.0-and-0bsd
+license_link: https://huggingface.co/codegeist/codegeist-llm/blob/main/THIRD_PARTY_NOTICES.md
 tags:
+- gguf
+- q4_k_m
+- docker-model-runner
 - peft
 - lora
-- sft
-- transformers
-- unsloth
 - codegeist-training
-- initial-training
 ---
 
-# Codegeist LLM Qwen3-1.7B Training Adapter
+# Codegeist LLM Qwen3-1.7B Artifacts
 
-This LoRA adapter is the first completed Codegeist training stage. It establishes
-the model identity with the first approved training record:
+This experimental release adds one complete merged Q4_K_M GGUF for Docker Model
+Runner while retaining the original first-stage PEFT adapter.
 
 ```text
 User: What is Codegeist?
 Assistant: Codegeist is a coding agent created by René Schmidt.
 ```
 
-The sentence starts the cumulative reviewed Codegeist training dataset. Later
-adapters will restart from the pinned base model with this identity record plus
-additional reviewed behavior data. This adapter is not used as a checkpoint for
-subsequent training.
-
-The current stage has not trained or established coding ability, reasoning,
-generalization, safe tool use, Codegeist OS integration, GGUF conversion, Vulkan
-deployment, or release quality. Those capabilities require later training and
-held-out evaluation.
-
-## Artifact Identity
+## GGUF Identity
 
 | Field | Value |
 | --- | --- |
-| Release | `v0.2.1` |
-| Base model | `Qwen/Qwen3-1.7B` |
+| Release | `v0.3.0-alpha.1` |
+| File | `gguf/codegeist-llm-Q4_K_M.gguf` |
+| Size | `1107408608` bytes |
+| SHA-256 | `869a74e12cecb8bb3baf33bb28524630ba3c183da765253def48183a359d5544` |
+| Quantization | `Q4_K_M` without an importance matrix |
 | Base revision | `70d244cc86ccca08cf5af4e1e306ecf908b1ad5e` |
-| Adapter format | PEFT LoRA, Safetensors |
-| Adapter weight SHA-256 | `4cc89bd25712ff4f532c1eaaa5c8086dc344a05b0778d2a304b8ff7a2efaf4a7` |
-| Adapter artifact revision | `a9504a0ee1150ea05f88ff725758404fcb604a32` |
-| Training Job | `6a76c9983e1f34a7e32be58c` |
-| Training date | 2026-08-08 |
-
-`v0.2.1` is a metadata-only release. Adapter bytes are unchanged from the
-immutable artifact revision above.
-
-`evidence.json`, `attribution-training-result.json`,
-`attribution-gpu-test-result.json`, and `publication.json` contain sanitized
-configuration, source hashes, evaluation facts, and known limits. They contain
-no private logs or credentials.
-
-## Intended Use
-
-Use this release to reproduce, inspect, and verify the first Codegeist training
-stage. Pin the exact base and adapter revisions above.
-
-Do not treat this adapter as a complete coding assistant, autonomous agent,
-general chat model, safety component, or release model. Those behaviors were not
-trained or evaluated in this stage.
-
-## Loading
-
-This example requires a CUDA GPU with BF16 support and has no CPU fallback. It
-pins the immutable commit that introduced the adapter weights.
-
-```python
-import os
-
-os.environ["HF_HUB_DISABLE_IMPLICIT_TOKEN"] = "1"
-
-import torch
-from peft import PeftModel
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-BASE_MODEL = "Qwen/Qwen3-1.7B"
-BASE_REVISION = "70d244cc86ccca08cf5af4e1e306ecf908b1ad5e"
-ADAPTER_MODEL = "codegeist/codegeist-llm"
-ADAPTER_REVISION = "a9504a0ee1150ea05f88ff725758404fcb604a32"
-
-tokenizer = AutoTokenizer.from_pretrained(
-    BASE_MODEL,
-    revision=BASE_REVISION,
-    trust_remote_code=False,
-    token=False,
-)
-base_model = AutoModelForCausalLM.from_pretrained(
-    BASE_MODEL,
-    revision=BASE_REVISION,
-    trust_remote_code=False,
-    dtype=torch.bfloat16,
-    low_cpu_mem_usage=True,
-    token=False,
-).to("cuda")
-model = PeftModel.from_pretrained(
-    base_model,
-    ADAPTER_MODEL,
-    revision=ADAPTER_REVISION,
-    is_trainable=False,
-    token=False,
-).to(device="cuda", dtype=torch.bfloat16)
+| Adapter revision | `a9504a0ee1150ea05f88ff725758404fcb604a32` |
+| llama.cpp | `08659901c43b51de735740f1cf61bb82fbe0c4e4` |
 
-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)
-inputs = {name: tensor.to("cuda") for name, tensor in inputs.items()}
-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,
-    )
+## Docker Model Runner
 
-response = tokenizer.decode(
-    output[0, inputs["input_ids"].shape[1]:],
-    skip_special_tokens=True,
-).strip()
-print(response)
-```
-
-Expected response:
+The short command selects Q4_K_M from the mutable Hub `main` revision:
 
-```text
-Codegeist is a coding agent created by René Schmidt.
+```bash
+docker model run hf.co/codegeist/codegeist-llm:Q4_K_M   "What is Codegeist?"
 ```
 
-## First Training Record
-
-```json
-{
-  "instruction": "What is Codegeist?",
-  "response": "Codegeist is a coding agent created by René Schmidt."
-}
-```
-
-The record ID is `codegeist-attribution-v2-001`. The creator explicitly approved
-the public wording and spelling. The record contains no contact details, user
-data, logs, or credentials.
-
-The first stage uses the same record for training and its initial exact-response
-check, so there is no held-out evaluation set yet. Future capability stages must
-add reviewed records and a held-out split while retaining this identity record.
+Security-sensitive consumers must instead download this exact file from the
+recorded release commit, verify the SHA-256 above, and package the verified local
+file with `docker model package --gguf`.
 
-## Training
+## Scope And Limits
 
-- Python 3.12.12
-- 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 `2.494612373970449`. The final logged step loss
-was `0.01821`.
-
-## Evaluation
-
-The adapter was loaded onto a fresh instance of the exact base revision in a
-separate process. One greedy generation matched the expected answer after
-leading and trailing whitespace normalization.
-
-The training Job completed after 133 reported running seconds. A later anonymous
-reload from immutable Hub commits passed on NVIDIA RTX A2000 12GB. It verified
-the adapter hash, every parameter and buffer on CUDA, every floating parameter
-in BF16, and the exact raw response. Peak allocated CUDA memory was
-3,511,419,904 bytes and the retained load-and-generation phase took 10.726
-seconds.
+The first adapter and this merged GGUF establish model identity only. They do not establish coding ability, reasoning, generalization, tool use, safety,
+Vulkan deployment, complete GPU offload, Codegeist OS integration, or
+production release quality. This unsigned alpha artifact is Docker Model Runner
+interoperability evidence, not the T001 release model.
 
 ## 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).
-
-## Current Limits
-
-- Downloaded base-model cache bytes were not independently rehashed during the
-  training Job; the model revision and upstream manifest remain immutable.
-- Repeat training, held-out evaluation, deterministic PyTorch algorithms,
-  coding benchmarks, safety evaluation, and generalization were not completed
-  in this stage.
+The merged GGUF includes Qwen3-1.7B weights distributed by Qwen under
+Apache-2.0. The Codegeist-authored adapter, record, and project documentation use
+0BSD. See `THIRD_PARTY_NOTICES.md`, `gguf/QWEN3-1.7B-LICENSE.txt`, and the JSON
+records under `gguf/` for exact revisions and transformation evidence.

SHA256SUMS

@@ -1,9 +1,14 @@
 9a66ed1f77d750a879b0e7b610bb15bb7c109fc1158448c0d7d543e7dbef421f  LICENSE
-a525f02a3bf4582dbc953ba6033328bd5762959c38988c20fe21daf8c777e14c  README.md
-d7ba9293f1820c63fe9e361ab3028390ce646125c898c008a4f8278eed8a4cb5  THIRD_PARTY_NOTICES.md
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 250c09d73c84a0eaf1c3955bc2bf4e29ea7c4896a715e1e115782890e5c7bb30  adapter_config.json
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-9bbde3787a225d1f8a2d864739faefd221e840a94c44c8a860d8c46b6991cdc9  evidence.json
-25e91fd971bbb1a64b107fe67f0e6580b60bf5b846ded060ebdd55faebc9ea16  attribution-training-result.json
 af0092e72bd347d5a4dd4bfbb579bae0402c51ead31959d33dd5647d4e34a430  attribution-gpu-test-result.json
-ea5216b7f84d53ebe4b5ff29d5f4c3dfd95b64f2af19f60dd52569664ad71fe6  publication.json
+25e91fd971bbb1a64b107fe67f0e6580b60bf5b846ded060ebdd55faebc9ea16  attribution-training-result.json
+9bbde3787a225d1f8a2d864739faefd221e840a94c44c8a860d8c46b6991cdc9  evidence.json
+832dd9e00a68dd83b3c3fb9f5588dad7dcf337a0db50f7d9483f310cd292e92e  gguf/QWEN3-1.7B-LICENSE.txt
+81a97a9b96b9b704fe41712c53e36b8b12f3b8b6dd1d25997650c6770b376342  gguf/SHA256SUMS
+928bc932b8f1d542e9ffeb2d1ba39d61e4af02cecad4f1a658afc5a37392efad  gguf/build.json
+869a74e12cecb8bb3baf33bb28524630ba3c183da765253def48183a359d5544  gguf/codegeist-llm-Q4_K_M.gguf
+759eb5e05df749af4613d3db05c95987851456eb091e206279690defa48a8b70  gguf/validation.json
+92dc3cb63928aa7dd8212d39c17887037f7a97951e39cde4cfc81b71975fadff  publication.json

THIRD_PARTY_NOTICES.md

@@ -2,15 +2,14 @@
 
 ## Qwen3-1.7B
 
-This repository contains a LoRA adapter for, but does not redistribute, the
-following base model:
+This repository redistributes one quantized GGUF derived from:
 
 - Model: `Qwen/Qwen3-1.7B`
 - Publisher: Qwen
 - Revision: `70d244cc86ccca08cf5af4e1e306ecf908b1ad5e`
 - License: Apache-2.0
 - Source: https://huggingface.co/Qwen/Qwen3-1.7B/tree/70d244cc86ccca08cf5af4e1e306ecf908b1ad5e
-- License text: https://huggingface.co/Qwen/Qwen3-1.7B/blob/70d244cc86ccca08cf5af4e1e306ecf908b1ad5e/LICENSE
 
-Users must obtain the base model separately and comply with its license and
-applicable terms.
+The exact upstream license text is included at
+`gguf/QWEN3-1.7B-LICENSE.txt`. The Codegeist adapter and authored metadata use
+0BSD; that license does not relicense the upstream Qwen weights.

gguf/QWEN3-1.7B-LICENSE.txt

@@ -0,0 +1,202 @@
+
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gguf/SHA256SUMS

@@ -0,0 +1,4 @@
+832dd9e00a68dd83b3c3fb9f5588dad7dcf337a0db50f7d9483f310cd292e92e  QWEN3-1.7B-LICENSE.txt
+928bc932b8f1d542e9ffeb2d1ba39d61e4af02cecad4f1a658afc5a37392efad  build.json
+869a74e12cecb8bb3baf33bb28524630ba3c183da765253def48183a359d5544  codegeist-llm-Q4_K_M.gguf
+759eb5e05df749af4613d3db05c95987851456eb091e206279690defa48a8b70  validation.json

gguf/build.json

@@ -0,0 +1,91 @@
+{
+  "artifact": {
+    "importance_matrix": null,
+    "path": "gguf/codegeist-llm-Q4_K_M.gguf",
+    "quantization": "Q4_K_M",
+    "sha256": "869a74e12cecb8bb3baf33bb28524630ba3c183da765253def48183a359d5544",
+    "size_bytes": 1107408608
+  },
+  "commands": {
+    "conversion": [
+      "uv",
+      "run",
+      "--project",
+      "/home/test/Projects/codegeist-ai/codegeist-llm/jobs/gguf/conversion",
+      "--frozen",
+      "--no-dev",
+      "--python",
+      "3.12.12",
+      "python",
+      "/home/test/Projects/codegeist-ai/codegeist-llm/.artifacts/gguf/build-c/private/toolchain/source/llama.cpp-08659901c43b51de735740f1cf61bb82fbe0c4e4/convert_hf_to_gguf.py",
+      "--outfile",
+      "/home/test/Projects/codegeist-ai/codegeist-llm/.artifacts/gguf/build-c/private/codegeist-llm-BF16.gguf",
+      "--outtype",
+      "bf16",
+      "/home/test/Projects/codegeist-ai/codegeist-llm/.artifacts/gguf/build-c/private/merged"
+    ],
+    "quantization": [
+      "/home/test/Projects/codegeist-ai/codegeist-llm/.artifacts/gguf/build-c/private/toolchain/binary/llama-b10333/llama-quantize",
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+      "Q4_K_M",
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+      "binary_url": "https://github.com/ggml-org/llama.cpp/releases/download/b10333/llama-b10333-bin-ubuntu-x64.tar.gz",
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+}

gguf/codegeist-llm-Q4_K_M.gguf

@@ -0,0 +1,3 @@
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+oid sha256:869a74e12cecb8bb3baf33bb28524630ba3c183da765253def48183a359d5544
+size 1107408608

gguf/validation.json

@@ -0,0 +1,34 @@
+{
+  "expected_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt.",
+  "normalization": "strip whitespace and remove the trailing llama.cpp runtime end marker",
+  "prompt": "What is Codegeist?",
+  "result": "passed",
+  "schema_version": 1,
+  "stages": {
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+      "normalized_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt.",
+      "raw_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt."
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+      "normalized_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt.",
+      "raw_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt."
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+      "normalized_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt.",
+      "raw_response": "Codegeist is a coding agent created by Ren\u00e9 Schmidt. [end of text]\n\n\n",
+      "runtime_end_marker_removed": "[end of text]"
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+}

publication.json

@@ -1,45 +1,21 @@
 {
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-  "target_release": "v0.2.1",
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     "id": "Qwen/Qwen3-1.7B",
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-    "license": "apache-2.0"
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   },
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-    "Replace the generated boilerplate README with a reviewed model card.",
-    "Set adapter_config.json revision to the immutable base revision used by the training Job.",
-    "Add sanitized Codegeist training evidence and a SHA-256 manifest.",
-    "Classify the adapter as the first Codegeist training stage without changing adapter bytes."
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+  "repository": "codegeist/codegeist-llm",
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+  "target_release": "v0.3.0-alpha.1"
 }