What are the hardware requirements for Alpaca 13B Lora?

Alpaca 13B Lora requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Alpaca 13B Lora and how large is it?

Alpaca 13B Lora is developed by yahma, a model with 13b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Alpaca 13B Lora perform on standard benchmarks?

Alpaca 13B Lora has the following published scores: LMSYS ELO 1068. Compare against reference models on this page or on the LLM Explorer leaderboards.

Alpaca 13B Lora by yahma — VRAM 0.1GB

Name: Alpaca 13B Lora
Author: yahma

Alpaca 13B Lora is an open-source language model by yahma. Features: 13b LLM, VRAM: 0.1GB, License: mit, LLM Explorer Score: 0.17, ELO: 1068.

Adapter Dataset:yahma/alpaca-cleaned Finetuned Lora Region:us

Model Card on HF 🤗: https://huggingface.co/yahma/alpaca-13b-lora

Alpaca 13B Lora Benchmarks

LMSys ELO 1068 vs 1272 (so35) -16%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Alpaca 13B Lora Parameters and Internals

Model Type

Low-Rank Adapter

Additional Notes

This adapter uses the Cleaned Alpaca dataset with new GPT-4 data.

Training Details

Data Sources:

yahma/alpaca-cleaned

Methodology:

Low-rank adaptation with LORA

Context Length:

512

LLM Name	Alpaca 13B Lora
Repository 🤗	https://huggingface.co/yahma/alpaca-13b-lora
Model Size	13b
Required VRAM	0.1 GB
Updated	2026-07-16
Maintainer	yahma
Model Files	0.1 GB
Model Architecture	Adapter
License	mit
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|k_proj\|v_proj\|o_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	16

Rank the Alpaca 13B Lora 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

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Note: green Score (e.g. "73.2") means that the model is better than yahma/alpaca-13b-lora.