<!-- SC_OFF --><div class="md"><p><a href="https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF">https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF</a></p> <p><a
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1satqwf/gemma_4_has_been_abliterated/"> <img alt="Gemma 4 has been abliterated"
<!-- SC_OFF --><div class="md"><p>I'm continuing to play around with local llms on my framework13 laptop. </p> <p>So, limited memory bandwith and processing power means exploring
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1tg7s7j/gemma4gembrain31bituncensoredheretic_is_out_now_a/"> <img
<!-- SC_OFF --><div class="md"><p>I run Gemma 4 26B-A4B locally via Ollama as part of a custom self-hosted AI platform. The platform stores every model interaction in SQLite,
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1seua77/gemma_4_31b_gguf_quants_ranked_by_kl_divergence/"> <img alt="Gemma 4 31B GGUF quants ranked by KL
<!-- SC_OFF --><div class="md"><p>Embedding layers are sensitive to quantization and Gemma 4 E2B/E4B have a ton of those which bloat the model parameter counts to 5B/10B. Makes
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1tpp2vp/gemma4harmonia31buncensoredheretic_is_out_now_a/"> <img alt="Gemma-4-Harmonia-31B-Uncensored-Heretic
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