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Adds support for gemma_270m to checkpoint converter #2380

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Adds support for gemma_270m to checkpoint converter #2380

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e6ba5b2
Adds support for gemma_270m to checkpoint converter
JyotinderSingh Sep 1, 2025
451f6a5
format
JyotinderSingh Sep 1, 2025
082ae31
removes assertion
JyotinderSingh Sep 8, 2025
53646be
format
JyotinderSingh Sep 9, 2025
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29 changes: 29 additions & 0 deletions .vscode/launch.json
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Original file line number Diff line number Diff line change
@@ -0,0 +1,29 @@
{
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Remove? Or add to .gitignore?

// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Pytest: Prompt for test target",
"type": "debugpy",
"request": "launch",
"module": "pytest",
"console": "integratedTerminal",
"justMyCode": true,
"args": [
"${input:pytestTarget}"
]
}
],

// 2. This 'inputs' array defines the prompt
"inputs": [
{
"id": "pytestTarget",
"type": "promptString",
"description": "Enter the pytest target (file path or file::function)",
"default": ""
}
]
}
18 changes: 13 additions & 5 deletions tools/checkpoint_conversion/convert_gemma3_checkpoints.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,8 @@
Usage:
```shell
cd tools/checkpoint_conversion
python convert_gemma_checkpoints.py --preset gemma3_instruct_1b
python convert_gemma_checkpoints.py --preset gemma3_instruct_4b
python convert_gemma3_checkpoints.py --preset gemma3_instruct_1b
python convert_gemma3_checkpoints.py --preset gemma3_instruct_4b
```
"""

Expand Down Expand Up @@ -43,6 +43,15 @@

PRESET_MAP = {
# === Text ===
# 270M
"gemma3_instruct_270m": {
"model": gm.nn.Gemma3_270M,
"params": gm.ckpts.CheckpointPath.GEMMA3_270M_IT,
},
"gemma3_270m": {
"model": gm.nn.Gemma3_270M,
"params": gm.ckpts.CheckpointPath.GEMMA3_270M_PT,
},
# 1B
"gemma3_1b": {
"model": gm.nn.Gemma3_1B,
Expand Down Expand Up @@ -493,7 +502,6 @@ def validate_output(
params=flax_params,
multi_turn=False,
cache_length=256 if length <= 256 else 512,
# max_out_length=length,
)
flax_output = flax_sampler.chat(input_str, images=image)
print("🔶 Flax output:", flax_output)
Expand All @@ -508,11 +516,11 @@ def main(_):
assert preset in presets, (
f"Invalid preset {preset}. Must be one of {','.join(presets)}"
)
text_only = "text" in preset or "1b" in preset
text_only = "text" in preset or "1b" in preset or "270m" in preset

print("🏃 Loading Flax model and tokeniser")
flax_kwargs = {}
if text_only and "1b" not in preset:
if text_only and "1b" not in preset and "270m" not in preset:
flax_kwargs["text_only"] = True
Comment on lines +519 to 524
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medium

The logic for determining if a model is text_only and if it needs the text_only kwarg for Flax is based on string matching in the preset name. This can be fragile and hard to maintain as new model sizes are added. To improve reusability and ensure all presets are handled robustly, consider making this information explicit in the PRESET_MAP.1

For example, you could add is_text_only and needs_flax_text_only_kwarg flags to each preset dictionary:

PRESET_MAP = {
    # ...
    "gemma3_instruct_270m": {
        "model": gm.nn.Gemma3_270M,
        "params": gm.ckpts.CheckpointPath.GEMMA3_270M_IT,
        "is_text_only": True,
        "needs_flax_text_only_kwarg": False,
    },
    "gemma3_4b_text": {
        "model": gm.nn.Gemma3_4B,
        "params": gm.ckpts.CheckpointPath.GEMMA3_4B_PT,
        "is_text_only": True,
        "needs_flax_text_only_kwarg": True,
    },
    # ...
}

Then, the logic in main() would be much cleaner and less error-prone when adding new presets.

Suggested change
text_only = "text" in preset or "1b" in preset or "270m" in preset
print("🏃 Loading Flax model and tokeniser")
flax_kwargs = {}
if text_only and "1b" not in preset:
if text_only and "1b" not in preset and "270m" not in preset:
flax_kwargs["text_only"] = True
preset_info = PRESET_MAP[preset]
text_only = preset_info.get("is_text_only", False)
print("🏃 Loading Flax model and tokeniser")
flax_kwargs = {}
if preset_info.get("needs_flax_text_only_kwarg", False):
flax_kwargs["text_only"] = True

Style Guide References

Footnotes

  1. Checkpoint conversion scripts should be reusable and able to handle all presets for a model. Relying on string matching in preset names can make the script less robust and harder to maintain when new presets are added. (link) ↩

flax_model = PRESET_MAP[preset]["model"](**flax_kwargs)
flax_config = flax_model.config
Expand Down
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