What are the hardware requirements for Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1?

Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 requires approximately 5.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1?

Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 by MinaMila — VRAM 5.2GB, 8K context

Name: Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1
Author: MinaMila

Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 is an open-source language model by MinaMila. Features: 2b LLM, VRAM: 5.2GB, Context: 8K, LLM Explorer Score: 0.18.

Arxiv:1910.09700 Conversational Endpoints compatible Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/MinaMila/gemma_unlearned_unbalance_gender_1e-7_1.0_0.25_0.5_epoch1

Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 Parameters and Internals

LLM Name	Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1
Repository 🤗	https://huggingface.co/MinaMila/gemma_unlearned_unbalance_gender_1e-7_1.0_0.25_0.5_epoch1
Model Size	2b
Required VRAM	5.2 GB
Updated	2026-01-03
Maintainer	MinaMila
Model Type	gemma2
Model Files	5.0 GB: 1-of-2 0.2 GB: 2-of-2
Model Architecture	Gemma2ForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.47.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma Unlearned Unbalance Gender 1e 7 1.0 0.25 0.5 Epoch1 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Note: green Score (e.g. "73.2") means that the model is better than MinaMila/gemma_unlearned_unbalance_gender_1e-7_1.0_0.25_0.5_epoch1.