What are the hardware requirements for Llama2 Finetune Alpaca Unsloth Minimal?

Llama2 Finetune Alpaca Unsloth Minimal requires approximately 13.5 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama2 Finetune Alpaca Unsloth Minimal and how large is it?

Llama2 Finetune Alpaca Unsloth Minimal is developed by delayedkarma, 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 Llama2 Finetune Alpaca Unsloth Minimal?

Llama2 Finetune Alpaca Unsloth Minimal is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama2 Finetune Alpaca Unsloth Minimal by delayedkarma — VRAM 13.5GB, 4K context

Name: Llama2 Finetune Alpaca Unsloth Minimal
Author: delayedkarma

Llama2 Finetune Alpaca Unsloth Minimal is an open-source language model by delayedkarma. Features: 7b LLM, VRAM: 13.5GB, Context: 4K, License: apache-2.0, Quantized, Fine-Tuned, LLM Explorer Score: 0.11.

4bit Base model:finetune:unsloth/ll... Base model:unsloth/llama-2-7b-... En Endpoints compatible Finetuned Llama Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/delayedkarma/llama2-finetune-alpaca-unsloth-minimal

Llama2 Finetune Alpaca Unsloth Minimal Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, llama, trl, sft

Additional Notes

A fine-tuned version of llama2 7b using the alpaca-cleaned dataset, and utilizing Unsloth. This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

Training Details

Data Sources:

alpaca-cleaned dataset

Methodology:

fine-tuning

Training Time:

2x faster

LLM Name	Llama2 Finetune Alpaca Unsloth Minimal
Repository 🤗	https://huggingface.co/delayedkarma/llama2-finetune-alpaca-unsloth-minimal
Base Model(s)	Llama 2 7B Bnb 4bit unsloth/llama-2-7b-bnb-4bit
Model Size	7b
Required VRAM	13.5 GB
Updated	2026-08-03
Maintainer	delayedkarma
Model Type	llama
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 3.6 GB: 3-of-3
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Llama2 Finetune Alpaca Unsloth Minimal 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 Llama2 Finetune Alpaca Unsloth Minimal

Best Alternatives	Context / RAM	Downloads	Likes
Smaugv0.1 6.0bpw H6 EXL2	195K / 26.4 GB	1	4
Smaugv0.1 5.0bpw H6 EXL2	195K / 22.3 GB	3	3
Smaugv0.1 4.65bpw H6 EXL2	195K / 20.8 GB	5	1
Smaugv0.1 4.0bpw H6 EXL2	195K / 18 GB	4	1
Smaugv0.1 8.0bpw H8 EXL2	195K / 34.9 GB	4	1
Smaugv0.1 3.0bpw H6 EXL2	195K / 13.9 GB	0	1
DeepSeek Prover V2 7B 4bit	64K / 3.9 GB	236	4
Mistral 7B Openplatypus 1K	32K / 29 GB	1814	0
Mistral 7B OpenOrca 1K	32K / 29 GB	1811	3
...rnlm2 20B Llama 4.0bpw H6 EXL2	32K / 11 GB	5	1

Note: green Score (e.g. "73.2") means that the model is better than delayedkarma/llama2-finetune-alpaca-unsloth-minimal.