Any-to-Any
MLX
Safetensors
gemma4
mlx-vlm
rlcd
multimodal
classification
parallel-inference
image-text-to-text
audio
video
4-bit precision
Instructions to use larkooo/gemma-e2b-rlcd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use larkooo/gemma-e2b-rlcd with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download larkooo/gemma-e2b-rlcd --local-dir gemma-e2b-rlcd
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 2,526 Bytes
53e24ca | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | import json
import pytest
from gemma_rlcd.core import Choice, Independent, Noul, Score
from gemma_rlcd.json_scoring import JSONField, candidate_fields, compile_field
class CharacterTokenizer:
def encode(self, text, **kwargs):
return list(map(ord, text))
def test_all_contracts_preserve_value_order_and_nested_fields():
questions = {
"animal": Choice("Pick one", {"cat": "cat", "dog": "dog"}),
"count": Score("Count", ["Zero", "One", "Two"]),
"present": Noul("Present?", {"false": "No", "true": "Yes"}),
"labels": Independent("Present?", {"dog": "A dog", "cat": "A cat"}),
}
fields = candidate_fields(questions)
assert [(field.path, field.values) for field in fields] == [
(("animal",), ("cat", "dog")),
(("count",), (0, 1, 2)),
(("present",), (False, True)),
(("labels", "dog"), (True, False)),
(("labels", "cat"), (True, False)),
]
@pytest.mark.parametrize("values", [(0, 1, 2), (True, False), ("cat", "catfish", 'cat "A"\n雪')])
def test_json_paths_and_complete_values_survive_token_compilation(values):
field = JSONField(('animal "kind"', "猫"), values)
compiled = compile_field(CharacterTokenizer(), field, "Assistant:\n")
for value, tail in zip(values, compiled.candidates, strict=True):
result = "".join(map(chr, compiled.prefix + tail)) + "}}"
assert json.loads(result) == {'animal "kind"': {"猫": value}}
def test_native_number_position_includes_expected_whitespace():
field = compile_field(CharacterTokenizer(), JSONField(("count",), tuple(range(10))), "")
assert "".join(map(chr, field.prefix)).endswith(": ")
assert ["".join(map(chr, candidate)) for candidate in field.candidates] == list("0123456789")
def test_shared_first_token_is_not_treated_as_a_complete_choice():
field = compile_field(
CharacterTokenizer(), JSONField(("label",), ("cat", "catfish", "dog")), ""
)
assert field.candidates[0][0] == field.candidates[1][0]
assert field.candidates[0] != field.candidates[1]
assert all(candidate[-1] == ord('"') for candidate in field.candidates)
def test_tokenizer_boundary_merges_fail_instead_of_scoring_wrong_position():
class MergingTokenizer(CharacterTokenizer):
def encode(self, text, **kwargs):
return super().encode(text.replace("x{", "X"), **kwargs)
with pytest.raises(ValueError, match="merged tokens"):
compile_field(MergingTokenizer(), JSONField(("label",), ("a", "b")), "x")
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