What are the hardware requirements for TR CPTs?

TR CPTs requires approximately 2.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed TR CPTs and how large is it?

TR CPTs is developed by Ba2han, a model with 1.5b 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 TR CPTs?

TR CPTs is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

TR CPTs by Ba2han — VRAM 2.9GB, 16K context

Name: TR CPTs
Author: Ba2han

TR CPTs is an open-source language model by Ba2han. Features: 1.5b LLM, VRAM: 2.9GB, Context: 16K, LLM Explorer Score: 0.29.

Base model:ba2han/random model Base model:finetune:ba2han/ran... Endpoints compatible Generated from trainer Qwen3 Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Ba2han/TR_CPTs

TR CPTs Parameters and Internals

LLM Name	TR CPTs
Repository 🤗	https://huggingface.co/Ba2han/TR_CPTs
Model Name	Ba2han/random_model
Base Model(s)	Ba2han/random_model Ba2han/random_model
Model Size	1.5b
Required VRAM	2.9 GB
Updated	2026-08-17
Maintainer	Ba2han
Model Type	qwen3
Model Files	2.9 GB 0.0 GB
Model Architecture	Qwen3ForCausalLM
Context Length	16384
Model Max Length	16384
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<pad>
Vocabulary Size	60800

Rank the TR CPTs 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

Best Alternatives to TR CPTs

Best Alternatives	Context / RAM	Downloads	Likes
Test CPTl	16K / 2.9 GB	1688	0

Note: green Score (e.g. "73.2") means that the model is better than Ba2han/TR_CPTs.