What are the hardware requirements for TiamaPY 1.1B V24?

TiamaPY 1.1B V24 requires approximately 2.2 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed TiamaPY 1.1B V24 and how large is it?

TiamaPY 1.1B V24 is developed by Ramikan-BR, a model with 1.1b 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 TiamaPY 1.1B V24?

TiamaPY 1.1B V24 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

TiamaPY 1.1B V24 by Ramikan-BR — VRAM 2.2GB, 4K context

Name: TiamaPY 1.1B V24
Author: Ramikan-BR

TiamaPY 1.1B V24 is an open-source language model by Ramikan-BR. Features: 1.1b LLM, VRAM: 2.2GB, Context: 4K, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

4bit Base model:finetune:unsloth/ti... Base model:unsloth/tinyllama-c... Conversational En Endpoints compatible Llama Pytorch Quantized Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Ramikan-BR/TiamaPY-1.1B-v24

TiamaPY 1.1B V24 Parameters and Internals

Model Type

text-generation-inference, transformers

Additional Notes

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

LLM Name	TiamaPY 1.1B V24
Repository 🤗	https://huggingface.co/Ramikan-BR/TiamaPY-1.1B-v24
Base Model(s)	Tinyllama Chat Bnb 4bit unsloth/tinyllama-chat-bnb-4bit
Model Size	1.1b
Required VRAM	2.2 GB
Updated	2026-08-04
Maintainer	Ramikan-BR
Model Type	llama
Model Files	2.2 GB 2.2 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the TiamaPY 1.1B V24 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

Quantized Models of the TiamaPY 1.1B V24

Model	Likes	Downloads	VRAM
TiamaPY 1.1B V24 Q8 0 GGUF	0	10	1 GB

Best Alternatives to TiamaPY 1.1B V24

Best Alternatives	Context / RAM	Downloads	Likes
...E TinyLlama 1.1B 32K Base 4bit	32K / 0.6 GB	17	1
...E TinyLlama 1.1B 32K Base 8bit	32K / 1.2 GB	17	1
...1B 32K Instruct 8.0bpw H8 EXL2	32K / 1.2 GB	6	1
...1B 32K Instruct 3.0bpw H6 EXL2	32K / 0.5 GB	6	0
Athena TinyLlama V0.1	16K / 2.2 GB	14	0
...lama PY CODER 4bit Lora 4k V12	4K / 2.2 GB	8	0
Tinyllama Coder Py V14	4K / 2.2 GB	5	0
...icipal Prediction Merged Model	4K / 2.2 GB	6	0
TiamaPY V27	4K / 2.2 GB	7	0
Merged 4bit Tiny Llama Gc2	4K / 0.8 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than Ramikan-BR/TiamaPY-1.1B-v24.