What are the hardware requirements for Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1?

Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 requires approximately 29.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1?

Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 by AmberYifan — VRAM 29.7GB, 32K context

Name: Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1
Author: AmberYifan

Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 is an open-source language model by AmberYifan. Features: 14b LLM, VRAM: 29.7GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.19.

Arxiv:2305.18290 Base model:amberyifan/qwen2.5-... Base model:finetune:amberyifan... Conversational Dpo Endpoints compatible Generated from trainer Instruct Qwen2 Region:us Safetensors Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/AmberYifan/Qwen2.5-14B-Instruct-wildfeedback-RPO-DRIFT-iter1

Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 Parameters and Internals

LLM Name	Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1
Repository 🤗	https://huggingface.co/AmberYifan/Qwen2.5-14B-Instruct-wildfeedback-RPO-DRIFT-iter1
Model Name	Qwen2.5-14B-Instruct-wildfeedback-RPO-DRIFT-iter1
Base Model(s)	AmberYifan/Qwen2.5-14B-Instruct-wildfeedback-seed-RPO-0.001 AmberYifan/Qwen2.5-14B-Instruct-wildfeedback-seed-RPO-0.001
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-05-29
Maintainer	AmberYifan
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.7 GB: 6-of-6 0.0 GB
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.53.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1 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 Qwen2.5 14B Instruct Wildfeedback RPO DRIFT Iter1

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than AmberYifan/Qwen2.5-14B-Instruct-wildfeedback-RPO-DRIFT-iter1.