Meta Llama 3.1 8B Instruct Bnb 4bit By unsloth: Benchmarks, Features and Detailed Analysis. Insights on Meta Llama 3.1 8B Instruct Bnb 4bit.

Arxiv:2204.05149 4-bit 4bit Autotrain compatible Base model:meta-llama/llama-3.... Base model:quantized:meta-llam... Bitsandbytes Conversational En Endpoints compatible Facebook Instruct Llama Llama-3 Meta Quantized Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit

Meta Llama 3.1 8B Instruct Bnb 4bit Benchmarks

LLME Score: 0.27718

^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)

Meta Llama 3.1 8B Instruct Bnb 4bit (unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit)

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Meta Llama 3.1 8B Instruct Bnb 4bit Parameters and Internals

Model Type

auto-regressive, transformer, instruction tuned, multilingual, text generation

Use Cases

Areas:

Commercial use, Research use, Education, Climate, Open innovation

Applications:

Chatbots, Synthetic data generation and distillation, Natural language generation tasks

Primary Use Cases:

Assistant-like chat, Multilingual dialogue applications

Limitations:

Use in unsupported languages without further tuning, Violation of laws, Out-of-scope uses as per Acceptable Use Policy

Considerations:

Comprehensive safety and performance testing required before deployment

Additional Notes

Model supports a longer context window and leverages Grouped-Query Attention for enhanced inference.

Supported Languages

English (fluent), German (fluent), French (fluent), Italian (fluent), Portuguese (fluent), Hindi (fluent), Spanish (fluent), Thai (fluent)

Training Details

Data Sources:

publicly available online data

Data Volume:

15 trillion tokens

Methodology:

Supervised fine-tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF)

Context Length:

128000

Training Time:

1.46M GPU hours for 8B

Hardware Used:

H100-80GB GPUs

Model Architecture:

Optimized transformer architecture using Grouped-Query Attention (GQA)

Safety Evaluation

Methodologies:

red-teaming, adversarial testing

Findings:

to be determined

Risk Categories:

misinformation, bias

Ethical Considerations:

Safety fine-tuning, safety datasets usage

Responsible Ai Considerations

Fairness:

Efforts were made to ensure fairness across languages and tasks

Transparency:

Model capabilities and limitations are communicated openly

Accountability:

Model provided with usage guides and responsible deployment methods

Mitigation Strategies:

Safety datasets, red-teaming, responsible use guides

Input Output

Input Format:

Multilingual text

Accepted Modalities:

text

Output Format:

Text and code

Performance Tips:

Ensure updated software and compatible hardware

Release Notes

Version:

3.1

Date:

July 23, 2024

Notes:

First release with multilingual support and instruction fine-tuning.

LLM Name	Meta Llama 3.1 8B Instruct Bnb 4bit
Repository 🤗	https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
Base Model(s)	meta-llama/Llama-3.1-8B-Instruct meta-llama/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	5.7 GB
Updated	2025-09-27
Maintainer	unsloth
Model Type	llama
Instruction-Based	Yes
Model Files	5.7 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	meta
Context Length	131072
Model Max Length	131072
Transformers Version	4.49.0.dev0
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Quantized Models of the Meta Llama 3.1 8B Instruct Bnb 4bit

Model	Likes	Downloads	VRAM
...ball Alpaca Llama3.1 8B Philos	1	0	16 GB
...leverBoi Llama 3.1 8B Instruct	1	468	0 GB
Ushistory Llama 3.1 8B	0	6	6 GB
FortyK Pretrained Merged Llama	0	5	16 GB
Llama Uft1.2 Persianqa	0	161	5 GB
Finetuned8b	0	5	16 GB
Loramerged	0	5	21 GB
Model	0	425	4 GB
Llama Uft7 Persianqa	0	63	5 GB
... 8B Instruct PRM800K Reasoning	1	3	16 GB

Best Alternatives to Meta Llama 3.1 8B Instruct Bnb 4bit

Best Alternatives	Context / RAM	Downloads	Likes
...B Instruct Gradient 1048K 4bit	1024K / 4.5 GB	6	2
...B Instruct Gradient 1048K 8bit	1024K / 8.6 GB	6	1
...truct Gradient 1048K Bpw6 EXL2	1024K / 6.7 GB	10	2
...truct Gradient 1048K Bpw5 EXL2	1024K / 5.8 GB	6	0
Llama 3 8B Instruct 1048K 4bit	1024K / 4.5 GB	172	25
Llama 3 8B Instruct 1048K 8bit	1024K / 8.6 GB	104	17
... Gradient 1048K 8.0bpw H8 EXL2	1024K / 8.6 GB	10	3
...ct Gradient 1048K Bpw2.25 EXL2	1024K / 3.4 GB	3	1
Llama 3 8B Instruct 262K 2bit	256K / 2.5 GB	7	1
...B Instruct 262k V2 EXL2 5.0bpw	256K / 5.8 GB	6	1

Rank the Meta Llama 3.1 8B Instruct Bnb 4bit Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Original data from HuggingFace, OpenCompass and various public git repos.

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