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Llama 3.2 3b Instruct Fp8 model by RedHatAI
⭐ 33.9
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Model

Llama 3.2 3b Instruct Fp8

by RedHatAI redhatai/llama-3.2-3b-instruct-fp8
Free2AITools Nexus Index
33.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 32
R: Recency 87
Q: Quality 65
Tech Context
3.61 Params
8.192K Ctx
Vital Performance
2.0K DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 33.9 FNI Score
3.61B Params
8k Context
2.0K Downloads
8G GPU ~4GB Est. VRAM
Dense LLAMAFORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID redhatai/llama-3.2-3b-instruct-fp8
Shape L28 D3072
Provider huggingface_deepspec
πŸ’Ύ

Compute Threshold

~4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{redhatai_llama_3_2_3b_instruct_fp8,
  author = {RedHatAI},
  title = {Llama 3.2 3b Instruct Fp8 Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/RedHatAI/Llama-3.2-3B-Instruct-FP8}},
  note = {Accessed via Free2AITools.}
}
APA Style
RedHatAI. (2024). Llama 3.2 3b Instruct Fp8 [Model]. Free2AITools. https://huggingface.co/RedHatAI/Llama-3.2-3B-Instruct-FP8

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run llama-3.2-3b-instruct-fp8
πŸ€— HF Download
huggingface-cli download redhatai/llama-3.2-3b-instruct-fp8

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 32
Recency (R) 87
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Llama 3.2 3b Instruct Fp8: Authority (A:0), Popularity (P:32), Recency (R:87), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Deployment reference

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Technical Deep Dive

Llama-3.2-3B-Instruct-FP8: 2.9B parameters, 131072 context length, llama architecture.

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
2.0KDownloads
Hub Discussions
πŸ“¦Data Source: huggingface_deepspec
πŸ”„ Updated daily

Source summary: Based on huggingface_deepspec metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--redhatai--llama-3.2-3b-instruct-fp8
slug
redhatai--llama-3.2-3b-instruct-fp8
source
huggingface_deepspec
author
RedHatAI
tags
llama, 2.9B, text-generation, safetensors, llama-3, neuralmagic, llmcompressor, conversational, en, de, fr, it, pt, hi, es, th, base_model:meta-llama/llama-3.2-3b-instruct, license:llama3.2, compressed-tensors, region:us

βš™οΈ Technical Specs

architecture
LlamaForCausalLM
params billions
3.61
context length
8,192
pipeline tag
text-generation
vram gb
4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
2,031
stars
0
forks
0

Data indexed from public sources. Updated daily.