What are the hardware requirements for Term Qwen2 7 Json Lora?

Term Qwen2 7 Json 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 Term Qwen2 7 Json Lora and how large is it?

Term Qwen2 7 Json Lora is developed by weiiv, 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 Term Qwen2 7 Json Lora?

Term Qwen2 7 Json Lora is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Term Qwen2 7 Json Lora by weiiv — VRAM 0.1GB

Name: Term Qwen2 7 Json Lora
Author: weiiv

Term Qwen2 7 Json Lora is an open-source language model by weiiv. Features: 7b LLM, VRAM: 0.1GB, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

Adapter Base model:adapter:qwen/qwen2-... Base model:qwen/qwen2-7b-instr... Finetuned Generated from trainer Gptq Instruct Llama-factory Lora Peft Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/weiiv/term_Qwen2_7_json_lora

Term Qwen2 7 Json Lora Parameters and Internals

Additional Notes

The model is a fine-tuned version using the PEFT library, focusing on specific hyperparameters such as learning rate and optimizer settings.

LLM Name	Term Qwen2 7 Json Lora
Repository 🤗	https://huggingface.co/weiiv/term_Qwen2_7_json_lora
Base Model(s)	Qwen2 7B Instruct GPTQ Int8 Qwen/Qwen2-7B-Instruct-GPTQ-Int8
Model Size	7b
Required VRAM	0.1 GB
Updated	2026-08-03
Maintainer	weiiv
Instruction-Based	Yes
Model Files	0.1 GB 0.0 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Adapter
License	other
Model Max Length	32768
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|o_proj\|k_proj\|gate_proj\|down_proj\|up_proj\|v_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	8
Errors	replace

Rank the Term Qwen2 7 Json Lora 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 weiiv/term_Qwen2_7_json_lora.