From 6a3127633de8855395ca09c692456952387bb141 Mon Sep 17 00:00:00 2001 From: Hal Eisen Date: Fri, 2 Oct 2026 19:07:54 -0700 Subject: [PATCH] ADFA-6321 | Add Qwen2.5-Coder 1.5B Instruct to the Get AI Models catalog Official Qwen GGUF, Q4_K_M, pinned to f86cb2c1. Gates 1, 2, 5, 6 and 7 checked against the Hugging Face API; gates 3 and 4 unproven like every other entry. --- plugins/Get-AI-Models/README.md | 5 +++-- plugins/Get-AI-Models/docs/CURATION.md | 14 ++++++++++---- plugins/Get-AI-Models/get-ai-models.html | 11 ++++++++++- .../src/main/assets/catalog/models.json | 17 +++++++++++++++++ 4 files changed, 40 insertions(+), 7 deletions(-) diff --git a/plugins/Get-AI-Models/README.md b/plugins/Get-AI-Models/README.md index d2ba62d6..87cc1520 100644 --- a/plugins/Get-AI-Models/README.md +++ b/plugins/Get-AI-Models/README.md @@ -140,8 +140,9 @@ explicitly, waiving the instruction-tuned, open-licence and 16k-context gates fo so `CatalogLoader` no longer enforces the licence or context gates, and the unit tests no longer assert them. `docs/CURATION.md` records exactly which gate each entry breaks. -Version 1.0.0 ships 6 files, all under 1 GB: Qwen2.5 0.5B (base), Qwen3 0.6B, Qwen3.5 0.8B, -Llama 3.2 1B Instruct, SmolLM2 360M Instruct, and H2O Danube3 500M (base). Five are Apache-2.0; +The catalog lists 7 files: Qwen2.5 0.5B (base), Qwen3 0.6B, Qwen3.5 0.8B, Llama 3.2 1B Instruct, +SmolLM2 360M Instruct, H2O Danube3 500M (base), all under 1 GB, and Qwen2.5-Coder 1.5B Instruct +(1.04 GiB), the only code-trained model. Six are Apache-2.0; Llama 3.2 1B is under the Llama 3.2 Community Licence. **The two behavioural gates are not yet proven.** Per the ticket, the admission harness that runs a diff --git a/plugins/Get-AI-Models/docs/CURATION.md b/plugins/Get-AI-Models/docs/CURATION.md index 1a2ea8c2..c875c588 100644 --- a/plugins/Get-AI-Models/docs/CURATION.md +++ b/plugins/Get-AI-Models/docs/CURATION.md @@ -58,9 +58,9 @@ All 12 entries passed that final HEAD cross-check, re-run after the most recent ## Catalog entries (maintainer-selected) -**This catalog is a maintainer override, not a gate-derived list.** The six models below were named -explicitly by the ticket owner, replacing the eleven gate-passing entries that shipped earlier. Three -of the six break at least one hard gate; those gates are therefore **no longer enforced** in +**This catalog is a maintainer override, not a gate-derived list.** The first six models below were +named explicitly by the ticket owner, replacing the eleven gate-passing entries that shipped +earlier; the seventh was requested later in ADFA-6321. Three of the six break at least one hard gate; those gates are therefore **no longer enforced** in `CatalogLoader` (licence, 16k context) nor asserted in `CatalogLoaderTest`. | Entry id | Base model | GGUF uploader | Ctx | Licence | Gate waived | @@ -71,8 +71,14 @@ of the six break at least one hard gate; those gates are therefore **no longer e | `llama-3-2-1b-instruct-q4_k_m` | `meta-llama/Llama-3.2-1B-Instruct` | unsloth | 131072 | llama3.2 | **2** (Llama 3.2 Community Licence; upstream repo gated) | | `smollm2-360m-instruct-q8_0` | `HuggingFaceTB/SmolLM2-360M-Instruct` | Hugging Face TB | 8192 | apache-2.0 | **7** (8192 context) | | `h2o-danube3-500m-base-q4_k_m` | `h2oai/h2o-danube3-500m-base` | mradermacher | 8192 | apache-2.0 | **1** (base model), **7** (8192 context) | +| `qwen2-5-coder-1-5b-instruct-q4_k_m` | `Qwen/Qwen2.5-Coder-1.5B-Instruct` | Qwen (Alibaba Cloud) | 32768 | apache-2.0 | none | -Gates 3 and 4 remain unproven for all six, as before. Gate 5 (chat template) does not apply to the +`qwen2-5-coder-1-5b-instruct-q4_k_m` was added by ADFA-6321: it is the only code-trained model in +the catalog. Its gates 1, 2, 5, 6 and 7 were re-checked against the API on 2026-10-02, and +`minRamBytes` is 4 GiB because it is the largest file here (1.04 GiB), one step above the 3 GiB of +the ~0.8 GB entries. + +Gates 3 and 4 remain unproven for all seven, as before. Gate 5 (chat template) does not apply to the two base models - they have none, which is part of why they are not usable as assistants. Gate 6 holds for every entry: single file, sha256 pinned to a commit revision, HEAD-verified. diff --git a/plugins/Get-AI-Models/get-ai-models.html b/plugins/Get-AI-Models/get-ai-models.html index 1f80fae4..2ff652dc 100644 --- a/plugins/Get-AI-Models/get-ai-models.html +++ b/plugins/Get-AI-Models/get-ai-models.html @@ -128,10 +128,19 @@

The catalog

apache-2.0 mradermacher + + Qwen2.5-Coder 1.5B Instruct + Q4_K_M + 1.5B + 1.04 GB + 32k + apache-2.0 + Qwen (Alibaba Cloud) +

Quantization is deliberately not restricted: Q4_K_M and Q8_0 both appear because the gates are about behaviour, not about a preferred format.

-

This list is a maintainer override, not a gate-derived set. Five entries are Apache-2.0; +

This list is a maintainer override, not a gate-derived set. Six entries are Apache-2.0; Llama 3.2 1B is under the Llama 3.2 Community Licence, whose upstream repo is also access-gated. Two entries are pretrained base models with no chat template, and two have an 8k context window. The licence and context gates are consequently no longer enforced in code - see diff --git a/plugins/Get-AI-Models/src/main/assets/catalog/models.json b/plugins/Get-AI-Models/src/main/assets/catalog/models.json index bcf56fa2..2bb26478 100644 --- a/plugins/Get-AI-Models/src/main/assets/catalog/models.json +++ b/plugins/Get-AI-Models/src/main/assets/catalog/models.json @@ -102,6 +102,23 @@ "baseModel": "h2oai/h2o-danube3-500m-base", "description": "H2O's small pretrained model, Apache-2.0. A base model, NOT instruction-tuned, so it continues text instead of answering, and it has an 8k context window. Strengths: very small, permissively licensed, trained on a well-described corpus. Weaknesses: unusable as an assistant as shipped, no chat template, no tool use, and below the 16k context floor. Listed at the ticket owner's request; it meets neither the instruction-tuned nor the context gate.", "behaviouralGatesVerified": false + }, + { + "id": "qwen2-5-coder-1-5b-instruct-q4_k_m", + "name": "Qwen2.5-Coder 1.5B Instruct", + "quantization": "Q4_K_M", + "parameters": "1.5B", + "fileName": "qwen2.5-coder-1.5b-instruct-q4_k_m.gguf", + "sizeBytes": 1117320768, + "sha256": "cc324af070c2ecbfd324a30884d2f951a7ff756aba85cb811a6ec436933bb046", + "url": "https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct-GGUF/resolve/f86cb2c1fa58255f8052cc32aeede1b7482d4361/qwen2.5-coder-1.5b-instruct-q4_k_m.gguf", + "minRamBytes": 4294967296, + "publisher": "Qwen (Alibaba Cloud) - official GGUF release", + "contextTokens": 32768, + "license": "apache-2.0", + "baseModel": "Qwen/Qwen2.5-Coder-1.5B-Instruct", + "description": "The only model here trained specifically on code, and the one to pick for help with Kotlin and Java. Strengths: noticeably better at code syntax and less prone to inventing APIs than the general chat models in this catalog, a 32k context window, a chat template with the Qwen tool-call format, and Apache-2.0 on both the model and the official GGUF. Weaknesses: the largest download here at about 1 GB, and it needs more memory than the sub-1B models, so it is slower on a mid-range phone; at 1.5B parameters with Q4_K_M rounding it still gets multi-step reasoning and less common libraries wrong, and it is weaker at general conversation than at code.", + "behaviouralGatesVerified": false } ] }