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gemma-3-270m-it

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This may not be seen, but it would be great to see some Gemma3 models tuned for text-embedding benchmarks (eg. MTEB Leaderboard). In most of my LLM work I use embedding models like the Qwen3-Embedding series, but there are currently very few high quality alternatives.

Thanks for the release :)

Hi @fahdmirzac ,

Thanks for your interest and great suggestion! We're actively evaluating possible directions for fine-tuning, including for embedding use cases. Your input helps guide priorities — much appreciated!

for some odd reasons I am getting stuck here

outputs = model.generate(**inputs, 
        max_new_tokens=256, 
        temperature=0.7, 
        do_sample=True,
        pad_token_id = tokenizer.eos_token_id)

Anyone else having this issue?