What are the hardware requirements for Medalpaca Lora 30B 8bit?

Medalpaca Lora 30B 8bit requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Medalpaca Lora 30B 8bit and how large is it?

Medalpaca Lora 30B 8bit is developed by medalpaca, a model with 30b 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 Medalpaca Lora 30B 8bit?

Medalpaca Lora 30B 8bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Medalpaca Lora 30B 8bit by medalpaca — VRAM 0.2GB

Name: Medalpaca Lora 30B 8bit
Author: medalpaca

Medalpaca Lora 30B 8bit is an open-source language model by medalpaca. Features: 30b LLM, VRAM: 0.2GB, License: cc, Quantized, LLM Explorer Score: 0.06.

Arxiv:2106.09685 Arxiv:2303.14070 8bit En Endpoints compatible Lora Medical Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/medalpaca/medalpaca-lora-30b-8bit

Medalpaca Lora 30B 8bit Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

medical domain tasks

Primary Use Cases:

question-answering, medical dialogue tasks

Limitations:

May not perform effectively outside medical domain, Primarily targets medical students' knowledge level, Not tested in real-world applications

Considerations:

It should not substitute a doctor's opinion.

Supported Languages

en (English)

Training Details

Data Sources:

Anki flashcards, Wikidoc, StackExchange, ChatDoctor dataset

Methodology:

LoRA fine-tuning and quantization

Model Architecture:

Based on LLaMA

LLM Name	Medalpaca Lora 30B 8bit
Repository 🤗	https://huggingface.co/medalpaca/medalpaca-lora-30b-8bit
Model Size	30b
Required VRAM	0.2 GB
Updated	2026-07-19
Maintainer	medalpaca
Model Files	0.2 GB
Supported Languages	en
Quantization Type	8bit
Model Architecture	AutoModel
License	cc
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	0.1
R Param	16

Rank the Medalpaca Lora 30B 8bit 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 medalpaca/medalpaca-lora-30b-8bit.