What are the hardware requirements for Qwen2 1.5B Instruct Function Calling V1?

Qwen2 1.5B Instruct Function Calling V1 requires approximately 6.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 1.5B Instruct Function Calling V1 and how large is it?

Qwen2 1.5B Instruct Function Calling V1 is developed by devanshamin, 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 1.5B Instruct Function Calling V1?

Qwen2 1.5B Instruct Function Calling V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2 1.5B Instruct Function Calling V1 by devanshamin — VRAM 6.2GB

Name: Qwen2 1.5B Instruct Function Calling V1
Author: devanshamin

Qwen2 1.5B Instruct Function Calling V1 is an open-source language model by devanshamin. Features: 1.5b LLM, VRAM: 6.2GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

Adapter Base model:adapter:qwen/qwen2-... Base model:qwen/qwen2-1.5b-ins... Conversational Dataset:devanshamin/gem-viggo-... Finetuned Generated from trainer Instruct Lora Peft Qwen2 Region:us Safetensors Sft Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/devanshamin/Qwen2-1.5B-Instruct-Function-Calling-v1

Qwen2 1.5B Instruct Function Calling V1 Parameters and Internals

Model Type

text-generation

Additional Notes

The model adds a chat template to the tokenizer configuration that supports multiple tools, but the fine-tuning was specifically on a dataset that uses a single tool. Various usage examples including tool usage for function calling have been provided.

Training Details

Data Sources:

devanshamin/gem-viggo-function-calling

LLM Name	Qwen2 1.5B Instruct Function Calling V1
Repository 🤗	https://huggingface.co/devanshamin/Qwen2-1.5B-Instruct-Function-Calling-v1
Base Model(s)	Qwen/Qwen2-1.5B-Instruct Qwen/Qwen2-1.5B-Instruct
Model Size	1.5b
Required VRAM	6.2 GB
Updated	2026-08-01
Maintainer	devanshamin
Instruction-Based	Yes
Model Files	0.1 GB 5.0 GB: 1-of-2 1.2 GB: 2-of-2 0.0 GB
Model Architecture	Adapter
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	down_proj\|gate_proj\|up_proj
LoRA Alpha	64
LoRA Dropout	0.05
R Param	32
Errors	replace

Rank the Qwen2 1.5B Instruct Function Calling V1 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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Note: green Score (e.g. "73.2") means that the model is better than devanshamin/Qwen2-1.5B-Instruct-Function-Calling-v1.