What are the hardware requirements for Mistral 7B Stop Hate?

Mistral 7B Stop Hate requires approximately 0.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral 7B Stop Hate and how large is it?

Mistral 7B Stop Hate is developed by irlab-udc, 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 Mistral 7B Stop Hate?

Mistral 7B Stop Hate is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B Stop Hate by irlab-udc — VRAM 0.3GB

Name: Mistral 7B Stop Hate
Author: irlab-udc

Mistral 7B Stop Hate is an open-source language model by irlab-udc. Features: 7b LLM, VRAM: 0.3GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

Arxiv:1910.09700 Arxiv:2410.00775 Adapter Base model:adapter:mistralai/m... Base model:mistralai/mistral-7... Conversational Dataset:irlab-udc/metahate En Finetuned Hate speech Instruct Lora Peft Region:us

Model Card on HF 🤗: https://huggingface.co/irlab-udc/Mistral-7b-Stop-Hate

Mistral 7B Stop Hate Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research

Applications:

conversational applications

Primary Use Cases:

stop hate speech generation

Limitations:

The model may carry biases present in the training data., It's not perfect and may continue some hate speech conversations.

Considerations:

Performance may vary across different domains.

Supported Languages

en (proficient)

Training Details

Data Sources:

irlab-udc/metahate

Methodology:

Using PEFT approach

Hardware Used:

NVIDIA RTX A6000

Responsible Ai Considerations

Fairness:

The model may carry biases present in the training data.

Mitigation Strategies:

The model is fine-tuned to prevent exacerbating hate discourse.

LLM Name	Mistral 7B Stop Hate
Repository 🤗	https://huggingface.co/irlab-udc/Mistral-7b-Stop-Hate
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.2 mistralai/Mistral-7B-Instruct-v0.2
Model Size	7b
Required VRAM	0.3 GB
Updated	2026-08-05
Maintainer	irlab-udc
Instruction-Based	Yes
Model Files	0.3 GB
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Model Max Length	512
Is Biased	lora_only
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	lm_head\|o_proj\|gate_proj\|v_proj\|up_proj\|q_proj\|down_proj\|k_proj
LoRA Alpha	64
LoRA Dropout	0.05
R Param	32

Rank the Mistral 7B Stop Hate 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 Mistral 7B Stop Hate

Best Alternatives	Context / RAM	Downloads	Likes
Qwen Megumin	0K / 0.1 GB	11	1
Mistral 7B Instruct Vi Alpaca	0K / 0.4 GB	5	0
Mistral 7B Instruct Sa V0.1	0K / 0 GB	9	0
Deepthink Reasoning Adapter	0K / 0.2 GB	16	3
Qwen2.5 7b NotesCorrector	0K / 0.6 GB	10	0
Mistral 7B Selfplay V0	0K / 0.2 GB	5	0
Mistral 7B V2 Selfplay	0K / 0.2 GB	7	0
...82 6142 45d8 9455 Bc68ca4866eb	0K / 1.2 GB	5	0
...Sql Flash Attention 2 Dataeval	0K / 1.9 GB	18	3
Text To Rule Mistral 2	0K / 0.3 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than irlab-udc/Mistral-7b-Stop-Hate.