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Tyness Boe 1.2b Pre Alpha Instruct model by jasonjimnz
⭐ 39
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Model

Tyness Boe 1.2b Pre Alpha Instruct

by jasonjimnz jasonjimnz/tyness-boe-1.2b-pre-alpha-instruct
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 5
R: Recency 100
Q: Quality 65
Tech Context
1.17 Params
4.096K Ctx
Vital Performance
52 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 1.17B Params
4k Context
52 Downloads
8G GPU ~3GB Est. VRAM
Dense LFM2FORCAUSALLM Architecture
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID jasonjimnz/tyness-boe-1.2b-pre-alpha-instruct
License Other
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.2GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{jasonjimnz_tyness_boe_1_2b_pre_alpha_instruct,
  author = {jasonjimnz},
  title = {Tyness Boe 1.2b Pre Alpha Instruct Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/jasonjimnz/tyness-boe-1.2b-pre-alpha-instruct}},
  note = {Accessed via Free2AITools.}
}
APA Style
jasonjimnz. (2026). Tyness Boe 1.2b Pre Alpha Instruct [Model]. Free2AITools. https://huggingface.co/jasonjimnz/tyness-boe-1.2b-pre-alpha-instruct

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run tyness-boe-1.2b-pre-alpha-instruct
πŸ€— HF Download
huggingface-cli download jasonjimnz/tyness-boe-1.2b-pre-alpha-instruct

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) 5
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Tyness Boe 1.2b Pre Alpha Instruct: Authority (A:0), Popularity (P:5), Recency (R:100), 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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⚠️ Incomplete Data

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

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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.

Social Proof

HuggingFace Hub
52Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face 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--jasonjimnz--tyness-boe-1.2b-pre-alpha-instruct
slug
jasonjimnz--tyness-boe-1.2b-pre-alpha-instruct
source
huggingface
author
jasonjimnz
license
Other
tags
peft, safetensors, gguf, lfm2, boe, spanish-law, legal, lora, qlora, sft, rag, grounded-generation, tyness-train, pre-alpha, question-answering, es, base_model:liquidai/lfm2.5-1.2b-instruct, base_model:adapter:liquidai/lfm2.5-1.2b-instruct, license:other, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

architecture
Lfm2ForCausalLM
params billions
1.17
context length
4,096
pipeline tag
question-answering
vram gb
2.2
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
52

Data indexed from public sources. Updated daily.