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base_model: google/gemma-4-E2B-it
library_name: transformers
pipeline_tag: text-classification
tags:
- gemma4
- sequence-classification
- text-classification
---
# Gemma 4 E2B IT Sequence Classification
This checkpoint converts `google/gemma-4-E2B-it` into a two-label sequence
classifier by slicing the original LM head to the single-token labels `no` and
`yes`.
The classifier logits are exactly the original next-token logits for:
- `no`: token id `1904`
- `yes`: token id `4443`
Load with custom code enabled:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_id = "baseten/gemma-4-e2b-it-sequence-classification"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(
model_id,
trust_remote_code=True,
dtype="auto",
)
```
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