What are the hardware requirements for Exp 2 Q R?

Exp 2 Q R requires approximately 15.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Exp 2 Q R and how large is it?

Exp 2 Q R is developed by ehristoforu, a model with 7.6b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Exp 2 Q R?

Exp 2 Q R is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Exp 2 Q R by ehristoforu — VRAM 15.2GB, 128K context

Name: Exp 2 Q R
Author: ehristoforu

Exp 2 Q R is an open-source language model by ehristoforu. Features: 7.6b LLM, VRAM: 15.2GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.15.

Base model:ehristoforu/exp-1-q... Base model:finetune:ehristofor... Conversational En Endpoints compatible Qwen2 Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/ehristoforu/exp-2-q-r

Exp 2 Q R Parameters and Internals

LLM Name	Exp 2 Q R
Repository 🤗	https://huggingface.co/ehristoforu/exp-2-q-r
Base Model(s)	Exp 1 Q R ehristoforu/exp-1-q-r
Model Size	7.6b
Required VRAM	15.2 GB
Updated	2026-07-23
Maintainer	ehristoforu
Model Type	qwen2
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Exp 2 Q R 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

Best Alternatives to Exp 2 Q R

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Quasar 3.7	986K / 15.2 GB	805	0
Quasar 3.3 Max	986K / 15.2 GB	132	0
MQ Coldbrew Base	128K / 15.2 GB	761	0
MawaredT1	128K / 15.2 GB	2318	1
Mergekit 01	128K / 16.2 GB	6	0
BBALAW1.6	128K / 15.2 GB	7	0
BBAI 525 Tsu GZ Xia0	128K / 15.2 GB	8	0
Nature Reason 1.2 Reallysmall	128K / 15.2 GB	27	1
Exp 3 Q R	128K / 15.2 GB	6	0
Math Custom Data	128K / 15.2 GB	11	0

Note: green Score (e.g. "73.2") means that the model is better than ehristoforu/exp-2-q-r.