What are the hardware requirements for Fraud Sentinel 1B?

Fraud Sentinel 1B requires approximately 0.7 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 Fraud Sentinel 1B and how large is it?

Fraud Sentinel 1B is developed by aniruddhabagal, a model with 1b 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 Fraud Sentinel 1B?

Fraud Sentinel 1B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Fraud Sentinel 1B by aniruddhabagal — VRAM 0.7GB, 128K context

Name: Fraud Sentinel 1B
Author: aniruddhabagal

Fraud Sentinel 1B is an open-source language model by aniruddhabagal. Features: 1b LLM, VRAM: 0.7GB, Context: 128K, License: llama3.2, Quantized, Instruction-Based, LLM Explorer Score: 0.31.

4-bit 4bit Base model:adapter:mlx-communi... Base model:mlx-community/llama... Conversational En Fraud-detection Instruct Llama Lora Mlx Prompt-injection Quantized Region:us Safetensors Structured-output

Model Card on HF 🤗: https://huggingface.co/aniruddhabagal/fraud-sentinel-1b

Fraud Sentinel 1B Parameters and Internals

LLM Name	Fraud Sentinel 1B
Repository 🤗	https://huggingface.co/aniruddhabagal/fraud-sentinel-1b
Base Model(s)	mlx-community/Llama-3.2-1B-Instruct-4bit mlx-community/Llama-3.2-1B-Instruct-4bit
Model Size	1b
Required VRAM	0.7 GB
Updated	2026-09-22
Maintainer	aniruddhabagal
Model Type	llama
Instruction-Based	Yes
Model Files	0.7 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	llama3.2
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.0.dev0
Tokenizer Class	TokenizersBackend
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Fraud Sentinel 1B capabilities

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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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