What are the hardware requirements for Llama3 Finetune 4bit?

Llama3 Finetune 4bit requires approximately 6.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama3 Finetune 4bit and how large is it?

Llama3 Finetune 4bit is developed by Sreevadan, a model with 4.6b 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 Llama3 Finetune 4bit?

Llama3 Finetune 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3 Finetune 4bit by Sreevadan — VRAM 6.1GB, 8K context

Name: Llama3 Finetune 4bit
Author: Sreevadan

Llama3 Finetune 4bit is an open-source language model by Sreevadan. Features: 4.6b LLM, VRAM: 6.1GB, Context: 8K, License: apache-2.0, Quantized, Fine-Tuned.

Arxiv:1910.09700 4-bit 4bit Autotrain compatible Bitsandbytes Dataset:open-orca/openorca Endpoints compatible Finetuned License:apache-2.0 Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Sreevadan/Llama3-finetune-4bit

Llama3 Finetune 4bit Parameters and Internals

LLM Name	Llama3 Finetune 4bit
Repository 🤗	https://huggingface.co/Sreevadan/Llama3-finetune-4bit
Model Size	4.6b
Required VRAM	6.1 GB
Updated	2024-07-04
Maintainer	Sreevadan
Model Type	llama
Model Files	5.0 GB: 1-of-2 1.1 GB: 2-of-2
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|reserved_special_token_250\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama3 Finetune 4bit 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

Best Alternatives to Llama3 Finetune 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Q4 Llama 3	8K / 6.1 GB	12	0
TinyLLama V0	2K / 0 GB	231176	45
SimpleLlamaSentences	2K / 0 GB	6	0
UniversalNER TinyLLama	2K / 0 GB	10	1
UniversalNER TinyLLama	2K / 0 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than Sreevadan/Llama3-finetune-4bit.