What are the hardware requirements for RAFT Llama3 Quantized 5epochs 24 06 04?

RAFT Llama3 Quantized 5epochs 24 06 04 requires approximately 5.8 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 RAFT Llama3 Quantized 5epochs 24 06 04 and how large is it?

RAFT Llama3 Quantized 5epochs 24 06 04 is developed by Vipinap, a model with 4.7b 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 RAFT Llama3 Quantized 5epochs 24 06 04?

RAFT Llama3 Quantized 5epochs 24 06 04 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RAFT Llama3 Quantized 5epochs 24 06 04 by Vipinap — VRAM 5.8GB, 8K context

Name: RAFT Llama3 Quantized 5epochs 24 06 04
Author: Vipinap

RAFT Llama3 Quantized 5epochs 24 06 04 is an open-source language model by Vipinap. Features: 4.7b LLM, VRAM: 5.8GB, Context: 8K, LLM Explorer Score: 0.13.

Arxiv:1910.09700 4-bit Autotrain compatible Bitsandbytes Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/Vipinap/RAFT_llama3_quantized_5epochs_24_06_04

RAFT Llama3 Quantized 5epochs 24 06 04 Benchmarks

LLME Score: 0.13476

^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)

RAFT Llama3 Quantized 5epochs 24 06 04 (Vipinap/RAFT_llama3_quantized_5epochs_24_06_04)

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RAFT Llama3 Quantized 5epochs 24 06 04 Parameters and Internals

Additional Notes

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. The model description and other specific sections require more information to be filled in.

LLM Name	RAFT Llama3 Quantized 5epochs 24 06 04
Repository 🤗	https://huggingface.co/Vipinap/RAFT_llama3_quantized_5epochs_24_06_04
Model Size	4.7b
Required VRAM	5.8 GB
Updated	2025-09-23
Maintainer	Vipinap
Model Type	llama
Model Files	4.7 GB: 1-of-2 1.1 GB: 2-of-2
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.39.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Best Alternatives to RAFT Llama3 Quantized 5epochs 24 06 04

Best Alternatives	Context / RAM	Downloads
...loth Llama3.1 Instruct Bnb4bit	128K / 5.8 GB	6
Hola	8K / 5.8 GB	5
Llama3.1 Merged	128K / 5.8 GB	6
EPFL TA Meister 4bit	8K / 5.8 GB	6
Book 4bitV5	8K / 5.8 GB	6

Note: green Score (e.g. "73.2") means that the model is better than Vipinap/RAFT_llama3_quantized_5epochs_24_06_04.

Rank the RAFT Llama3 Quantized 5epochs 24 06 04 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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RAFT Llama3 Quantized 5epochs 24 06 04 by Vipinap

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RAFT Llama3 Quantized 5epochs 24 06 04 Benchmarks

RAFT Llama3 Quantized 5epochs 24 06 04 Parameters and Internals

Best Alternatives to RAFT Llama3 Quantized 5epochs 24 06 04

Rank the RAFT Llama3 Quantized 5epochs 24 06 04 Capabilities

What open-source LLMs or SLMs are you in search of? 53999 in total.