What are the hardware requirements for Tinyllama Ft CodeAlpaca Adapter?

Tinyllama Ft CodeAlpaca Adapter requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tinyllama Ft CodeAlpaca Adapter and how large is it?

Tinyllama Ft CodeAlpaca Adapter is developed by mrm8488. 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 Tinyllama Ft CodeAlpaca Adapter?

Tinyllama Ft CodeAlpaca Adapter is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tinyllama Ft CodeAlpaca Adapter by mrm8488 — VRAM 0.1GB

Name: Tinyllama Ft CodeAlpaca Adapter
Author: mrm8488

Tinyllama Ft CodeAlpaca Adapter is an open-source language model by mrm8488. Features: LLM, VRAM: 0.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

4bit Adapter Base model:finetune:unsloth/ti... Base model:unsloth/tinyllama-b... Dataset:generator Finetuned Generated from trainer Lora Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mrm8488/tinyllama-ft-codeAlpaca-adapter

Tinyllama Ft CodeAlpaca Adapter Parameters and Internals

Additional Notes

This model is a fine-tuned version of the base model on the generator dataset with specified training hyperparameters.

Training Details

Data Sources:

generator

LLM Name	Tinyllama Ft CodeAlpaca Adapter
Repository 🤗	https://huggingface.co/mrm8488/tinyllama-ft-codeAlpaca-adapter
Base Model(s)	Tinyllama Bnb 4bit unsloth/tinyllama-bnb-4bit
Required VRAM	0.1 GB
Updated	2026-07-09
Maintainer	mrm8488
Model Files	0.1 GB
Quantization Type	4bit
Model Architecture	Adapter
License	apache-2.0
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|k_proj\|down_proj\|o_proj\|gate_proj\|v_proj\|up_proj
LoRA Alpha	32
LoRA Dropout	0
R Param	32

Rank the Tinyllama Ft CodeAlpaca Adapter 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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