| --- |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| tags: |
| - function-calling |
| - tool-use |
| - evaluation |
| - gemma4 |
| pretty_name: Gemma-4 Coder — tool-calling gate suite |
| configs: |
| - config_name: default |
| data_files: tool_eval_cases.jsonl |
| --- |
| |
| # Gemma-4 Coder — tool-calling gate suite |
|
|
| The 8-case eval behind the **tool-call pass rate** in our model cards' `model-index`: |
| positive prompts where the model must emit a structured tool call, plus a no-tool |
| **abstain** case (it must answer directly, not hallucinate a call). Use it to measure |
| any local tool-calling model the same way we do — or to reproduce our numbers. |
|
|
| ```python |
| from datasets import load_dataset |
| cases = load_dataset("tpls/gemma4-coder-tool-eval", split="train") # each: {name, user, tools, expect} |
| ``` |
|
|
| ## Scoring a model |
|
|
| Serve a GGUF on `llama.cpp` (`llama-server --jinja`), send each case's `user` + `tools` |
| the normal OpenAI way, and check the reply against `expect`. **Two rates**, because |
| `llama.cpp --jinja` doesn't recognise gemma-4's native tool-call markup: |
|
|
| - **raw** — llama.cpp's native parse. For gemma-4 it *structurally undercounts* (blind to the format). |
| - **shim** — the same outputs re-parsed for the native markup. This is the number that reflects training. |
|
|
| The shim is a tiny serve-side post-processor — ready-to-use (drop-in litellm callback + |
| a standalone parser, Apache-2.0) at **[`tpls/gemma4-tool-shim`](https://huggingface.co/tpls/gemma4-tool-shim)**, |
| where the recovery algorithm is also documented so you can re-implement it. |
|
|
| ```python |
| # sketch: per case, POST to your OpenAI-compatible endpoint, then |
| # raw_ok = response had a structured tool_call (or correctly abstained) |
| # shim_ok = same, after running the reply through the shim parser |
| # pass_rate = mean(ok over the 8 cases). expect == [] means "must NOT call a tool". |
| ``` |
|
|
| ## Files |
|
|
| | File | What | |
| |------|------| |
| | `tool_eval_cases.jsonl` | one case/line: `{name, user, tools, expect}` | |
| | `tool_calib.txt` | imatrix calibration text (code + tool-call markup) used when quantizing | |
|
|
| ## Scope & license |
|
|
| Authored by us, fully permissive (apache-2.0). This is an **eval** set, not training data — |
| our training mix is a derivative of public datasets and is **not** redistributed (its |
| reproducible recipe lives on each model card). Pairs with the |
| [`tpls/gemma4-tool-shim`](https://huggingface.co/tpls/gemma4-tool-shim) helper and the models below. |
|
|
| ## Used by |
|
|
| - [`tpls/Huihui-gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-GGUF`](https://huggingface.co/tpls/Huihui-gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-GGUF) |
| - [`tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-GGUF`](https://huggingface.co/tpls/gemma-4-12B-coder-fable5-composer2.5-v1-abliterated-GGUF) |
| - [`tpls/gemma-4-12B-coder-fable5-composer2.5-v1-sft-v5`](https://huggingface.co/tpls/gemma-4-12B-coder-fable5-composer2.5-v1-sft-v5) |
| - [`tpls/gemma-4-12B-coder-fable5-composer2.5-v1-sft-v5-GGUF`](https://huggingface.co/tpls/gemma-4-12B-coder-fable5-composer2.5-v1-sft-v5-GGUF) |
|
|
