What are the hardware requirements for Llama 7B Logicot?

Llama 7B Logicot requires approximately 1.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 7B Logicot and how large is it?

Llama 7B Logicot is developed by csitfun, a model with 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 Llama 7B Logicot?

Llama 7B Logicot is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 7B Logicot by csitfun — VRAM 1.1GB, 2K context

Name: Llama 7B Logicot
Author: csitfun

Llama 7B Logicot is an open-source language model by csitfun. Features: 7b LLM, VRAM: 1.1GB, Context: 2K, License: cc-by-sa-4.0, LLM Explorer Score: 0.07.

Dataset:csitfun/logicot En Endpoints compatible Llama Logical Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/datatune/llama-7b-logicot

Llama 7B Logicot Parameters and Internals

Model Type

text generation

Additional Notes

This model performs particularly well in logical reasoning tasks but has limitations in arithmetic as indicated by GSM8K scores.

Supported Languages

en (high)

Training Details

Data Sources:

GPT-4 alpaca data, LogiCoT

Methodology:

instruction-tuning

Training Time:

7 days total

Hardware Used:

2 A100 GPUs

LLM Name	Llama 7B Logicot
Repository 🤗	https://huggingface.co/datatune/llama-7b-logicot
Model Size	7b
Required VRAM	1.1 GB
Updated	2026-08-06
Maintainer	csitfun
Model Type	llama
Model Files	3.2 GB: 1-of-9 3.0 GB: 2-of-9 2.7 GB: 3-of-9 3.0 GB: 4-of-9 2.7 GB: 5-of-9 3.0 GB: 6-of-9 2.7 GB: 7-of-9 3.0 GB: 8-of-9 2.7 GB: 9-of-9 1.1 GB: 10-of-9 3.2 GB: 1-of-9 3.0 GB: 2-of-9 2.7 GB: 3-of-9 3.0 GB: 4-of-9 2.7 GB: 5-of-9 3.0 GB: 6-of-9 2.7 GB: 7-of-9 3.0 GB: 8-of-9 2.7 GB: 9-of-9 1.1 GB: 10-of-9 0.0 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	cc-by-sa-4.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.28.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32001
Torch Data Type	float32

Rank the Llama 7B Logicot capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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162	1024K / 16.1 GB	60
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118	1024K / 16.1 GB	15
A5.4	1024K / 16.1 GB	12
A3.4	1024K / 16.1 GB	13
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Note: green Score (e.g. "73.2") means that the model is better than datatune/llama-7b-logicot.