What are the hardware requirements for RasGulla1 7B?

RasGulla1 7B requires approximately 14.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed RasGulla1 7B and how large is it?

RasGulla1 7B is developed by AbacusResearch, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does RasGulla1 7B perform on standard benchmarks?

RasGulla1 7B has the following published scores: MMLU 64.94. Compare against reference models on this page or on the LLM Explorer leaderboards.

RasGulla1 7B by AbacusResearch — VRAM 14.4GB

Name: RasGulla1 7B
Author: AbacusResearch

RasGulla1 7B is an open-source language model by AbacusResearch. Features: 7b LLM, VRAM: 14.4GB, License: mit, Merged, LLM Explorer Score: 0.12, Arc: 69.7, HellaSwag: 87.4, MMLU: 64.9, GSM8K: 71.7.

Merged Model Cities Dataset:your dataset name En Endpoints compatible Finetuned Lora Mistral Region:us Safetensors Sharded Tensorflow Vendor-names Zip-codes

Model Card on HF 🤗: https://huggingface.co/AbacusResearch/RasGulla1-7b

RasGulla1 7B Parameters and Internals

Model Type

Text Classification

Use Cases

Areas:

Commercial Applications, Research

Applications:

Vendor Data Classification

Primary Use Cases:

Vendor identification by street and zip code

Additional Notes

This model uses only Lora weights and is specialized in identifying vendors based on street names, zip codes, and cities.

LLM Name	RasGulla1 7B
Repository 🤗	https://huggingface.co/AbacusResearch/RasGulla1-7b
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-10-09
Maintainer	AbacusResearch
Model Files	0.2 GB 2.0 GB: 1-of-8 2.0 GB: 2-of-8 1.9 GB: 3-of-8 1.7 GB: 4-of-8 1.9 GB: 5-of-8 2.0 GB: 6-of-8 1.9 GB: 7-of-8 1.0 GB: 8-of-8
Supported Languages	en
Model Architecture	AutoModelForCausalLM
License	mit
Is Biased	none
Tokenizer Class	LlamaTokenizer
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	up_proj\|down_proj\|v_proj\|q_proj\|k_proj\|gate_proj\|o_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the RasGulla1 7B 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 RasGulla1 7B

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B V0.3	32K / 14.5 GB	1366	5
Mistral 7B Instruct V0.3	32K / 14.5 GB	91	6
...unoichi Lemon Royale V3 32K 7B	32K / 14.5 GB	11	5
Mistral 7B Instruct V0.3	32K / 14.5 GB	1122	3
Mistralai Mistral 7B V0.3	32K / 14.5 GB	6	3
...ralai Mistral 7B Instruct V0.3	32K / 14.5 GB	6	3
Mistral 7B Instruct V0.3	32K / 14.5 GB	6	0
Mistral 7B V0.2	32K / 14.5 GB	66	1
Full V4 Astromistral Final	32K / 4.5 GB	6	1
LlamaGuard 7B	4K / 13.5 GB	4681	245

Note: green Score (e.g. "73.2") means that the model is better than AbacusResearch/RasGulla1-7b.