What are the hardware requirements for Qwen2 7B WAEMU Africa Banking Analysis?

Qwen2 7B WAEMU Africa Banking Analysis requires approximately 15.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 7B WAEMU Africa Banking Analysis and how large is it?

Qwen2 7B WAEMU Africa Banking Analysis is developed by Svngoku, a model with 7b 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 Qwen2 7B WAEMU Africa Banking Analysis?

Qwen2 7B WAEMU Africa Banking Analysis is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2 7B WAEMU Africa Banking Analysis by Svngoku — VRAM 15.2GB

Name: Qwen2 7B WAEMU Africa Banking Analysis
Author: Svngoku

Qwen2 7B WAEMU Africa Banking Analysis is an open-source language model by Svngoku. Features: 7b LLM, VRAM: 15.2GB, License: mit, Quantized, LLM Explorer Score: 0.13.

4bit Base model:finetune:unsloth/qw... Base model:unsloth/qwen2-7b-bn... Conversational Dataset:svngoku/waemu banking ... En Endpoints compatible Lora Pytorch Quantized Qwen2 Region:us Safetensors Sharded Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Svngoku/Qwen2-7b-WAEMU-Africa-Banking-Analysis

Qwen2 7B WAEMU Africa Banking Analysis Parameters and Internals

Model Type

text-generation-inference, transformers

Additional Notes

This Qwen2 model was trained with Unsloth and Huggingface's TRL library, achieving a training speed 2x faster.

Training Details

Data Sources:

Svngoku/WAEMU_Banking_Analysis

Methodology:

The model was trained using Unsloth and Huggingface's TRL library, which allowed for a training speed 2x faster.

LLM Name	Qwen2 7B WAEMU Africa Banking Analysis
Repository 🤗	https://huggingface.co/Svngoku/Qwen2-7b-WAEMU-Africa-Banking-Analysis
Base Model(s)	Qwen2 7B Bnb 4bit unsloth/Qwen2-7B-bnb-4bit
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-08-03
Maintainer	Svngoku
Model Files	0.2 GB 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
Quantization Type	4bit
Model Architecture	AutoModelForCausalLM
License	mit
Model Max Length	131072
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|k_proj\|q_proj\|o_proj\|down_proj\|up_proj\|gate_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16
Errors	replace

Rank the Qwen2 7B WAEMU Africa Banking Analysis 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 Qwen2 7B WAEMU Africa Banking Analysis

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Qwen2.5 8K Sports	0K / 15.2 GB	14	0
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Mistral 7B V0.3	0K / 14.5 GB	5	0
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Refined Llama3	0K / 0.2 GB	6	0
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Mistral 7B Instruct 4bit	0K / 0.2 GB	11	1

Note: green Score (e.g. "73.2") means that the model is better than Svngoku/Qwen2-7b-WAEMU-Africa-Banking-Analysis.