Gemma 4 E2B · Ollama

rubinmaximilian/Monk-Router-Gemma4e2b

A lightweight, hardware-aware router built on Gemma 4 E2B. It acts as a dispatcher for local AI setups, automatically deciding whether a prompt should run on edge hardware (like a Jetson Nano), a local GPU, or the cloud based on task complexity.

vision tools thinking

198 Pulls 1 Tag Updated 4 months ago

tripolskypetr/gemma4-uncensored-aggressive

Gemma 4 E2B-IT uncensored by HauhauCS. 0/465 Refusals

tools thinking

5,327 Pulls 1 Tag Updated 4 months ago

bjoernb/gemma4-e2b-fast

Gemma 4 E2B (Google DeepMind) with thinking mode disabled. Compact multimodal model — 2.3B effective / 5.1B total parameters. Supports text, image and audio input. Designed for edge devices and local deployment. Knowledge cutoff: January 2025.

vision tools thinking

1,780 Pulls 1 Tag Updated 4 months ago

MobiusDevelopment/gemma4-E2B-it-qat-Q4-unsloth-heretic

Gemma 4 models are designed to deliver frontier-level performance at each size. They are well-suited for reasoning, agentic workflows, coding, and multimodal understanding.

vision tools thinking

675 Pulls 1 Tag Updated 1 month ago

rafw007/gemma4-e2b-claude-coder

Fast, lightweight Gemma 4 E2B coding agent for Claude Code, 64K context, native tool-calling, 100% GPU on 16GB Apple Silicon.

vision tools thinking

843 Pulls 1 Tag Updated 2 months ago

cajina/gemma4_e2b-q2_k_xl

Based in gemma-4-E2B-it-UD-Q2_K_XL.gguf. Context 4096 and no thinking enabled in template.

tools thinking

620 Pulls 1 Tag Updated 3 months ago

bjoernb/gemma4-e2b-think

Gemma 4 E2B (Google DeepMind) with thinking mode enabled. Compact multimodal model — 2.3B effective / 5.1B total parameters. Supports text, image and audio input. Designed for edge devices and local deployment. Knowledge cutoff: January 2025.

vision tools thinking

460 Pulls 1 Tag Updated 4 months ago

lemeshkovalerij/gemma4-E2B-it-alpaca_adapetrs-q4_K_M

tools thinking

314 Pulls 1 Tag Updated 4 months ago

alicek0914/gemma4-scam

QLoRA fine-tune of Gemma 4 E2B for scam detection. F1 86.1% / FPR 1.1% on a 300-sample real test set. 12-tool function calling for SMS, email, voice transcripts, and OCR'd MMS images.

tools thinking

32 Pulls 1 Tag Updated 2 months ago

htunnthuthutech/gemma-4-e2b-aiops

A Q4_K_M GGUF of Gemma 4 E2B, fine-tuned on Apple Silicon (M3 Pro, 18 GB) using MLX LoRA to act as an autonomous AIOps Orchestrator Agent.

tools thinking

5 Pulls 1 Tag Updated 5 days ago

dzgg/Gemma-4-E2B-it-uncensored-GGUF

tools thinking

453 Pulls 2 Tags Updated 1 month ago

maxwell1500/psycho

A local-first psychology assistant fine-tuned from Gemma 4 on real therapy dialogues. Two model series: E2B (2.3B, 3.3–5.0 GB) and 12B (11.96B, 6.2–11.8 GB). 128K context. Legal Notice: Not a substitute for professional care.

tools thinking 12b

403 Pulls 11 Tags Updated 1 month ago

cmdmbox/skill-expert

Fine-tuned Gemma 4 E2B Q8 model for generating dense, production-ready `SKILL.md` files for autonomous AI agents

tools thinking

256 Pulls 1 Tag Updated 3 months ago

brinzaengineeringai/microlens-final

Gemma 4 E2B fine-tune for biological microscopy · 95 genera · 89% genus accuracy · runs offline · Apache-2.0 + CC-BY 4.0

vision tools thinking

7 Pulls 1 Tag Updated 2 months ago

evalengine/unbound-e2b

Uncensored on-device finetune of google/gemma-4-E2B-it by the Chromia and Eval Engine team

tools thinking

562 Pulls 1 Tag Updated 2 months ago

MobiusDevelopment/gemma-4-E2B-it-qat-q4_0-gguf

Gemma 4 models are designed to deliver frontier-level performance at each size. They are well-suited for reasoning, agentic workflows, coding, and multimodal understanding.

vision tools thinking

252 Pulls 1 Tag Updated 1 month ago

4skl/gemma4-e2b-mtp

Ultra-fast multimodal 2.3B Gemma 4 for on-device edge AI (3.7GB). Adds native vision/audio parsing to Unsloth Dynamic QAT with a 2-token MTP pipeline and a mobile-safe 32K context window. Perfect for smartphones and laptops sharing 8GB of total RAM.

vision tools thinking

401 Pulls 1 Tag Updated 2 weeks ago

cajina/gemma4_e2b-q4_k_s

Gemma4 model 2B parameters with Q4_K_S quatization. Thinking removed. Context set to 4096

tools thinking

1,216 Pulls 1 Tag Updated 3 months ago

bjoernb/gemma4-26b-think

Gemma 4 26B MoE (Google DeepMind) with thinking mode enabled. Mixture-of-Experts — 25.2B total / 3.8B active parameters, 256K context. Supports text and image input. Knowledge cutoff: January 2025.

vision tools thinking

2,750 Pulls 1 Tag Updated 4 months ago

bjoernb/gemma4-26b-fast

Gemma 4 26B MoE (Google DeepMind) with thinking mode disabled. Mixture-of-Experts — 25.2B total / 3.8B active parameters, 256K context. Supports text and image input. Knowledge cutoff: January 2025.

vision tools thinking

1,024 Pulls 1 Tag Updated 4 months ago