What are the hardware requirements for Qwen2.5 1.5B Cantoblanco Transporte En Lora?

Qwen2.5 1.5B Cantoblanco Transporte En Lora requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 1.5B Cantoblanco Transporte En Lora and how large is it?

Qwen2.5 1.5B Cantoblanco Transporte En Lora is developed by Bellido, 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 Qwen2.5 1.5B Cantoblanco Transporte En Lora?

Qwen2.5 1.5B Cantoblanco Transporte En Lora is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 1.5B Cantoblanco Transporte En Lora by Bellido — VRAM 0.1GB

Name: Qwen2.5 1.5B Cantoblanco Transporte En Lora
Author: Bellido

Qwen2.5 1.5B Cantoblanco Transporte En Lora is an open-source language model by Bellido. Features: 1.5b LLM, VRAM: 0.1GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.28.

Adapter Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-1.5b-i... Conversational Dataset:bellido/cantoblanco-tr... En Finetuned Instruct Lora Peft Qlora Qwen2 Region:us Safetensors Transport Workshop

Model Card on HF 🤗: https://huggingface.co/Bellido/qwen2.5-1.5b-cantoblanco-transporte-en-lora

Qwen2.5 1.5B Cantoblanco Transporte En Lora Parameters and Internals

LLM Name	Qwen2.5 1.5B Cantoblanco Transporte En Lora
Repository 🤗	https://huggingface.co/Bellido/qwen2.5-1.5b-cantoblanco-transporte-en-lora
Base Model(s)	Qwen/Qwen2.5-1.5B-Instruct Qwen/Qwen2.5-1.5B-Instruct
Model Size	1.5b
Required VRAM	0.1 GB
Updated	2026-10-14
Maintainer	Bellido
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Model Max Length	131072
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	gate_proj\|k_proj\|o_proj\|up_proj\|v_proj\|q_proj\|down_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16
Errors	replace

Rank the Qwen2.5 1.5B Cantoblanco Transporte En Lora capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
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Code Generation
Multi-Language Support and Translation

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