What are the hardware requirements for Mergekit Model Stock Wgpchvm?

Mergekit Model Stock Wgpchvm requires approximately 29.7 GB of VRAM and supports a context window of 986K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mergekit Model Stock Wgpchvm and how large is it?

Mergekit Model Stock Wgpchvm is developed by wanlige, a model with 14b 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 Mergekit Model Stock Wgpchvm?

Mergekit Model Stock Wgpchvm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mergekit Model Stock Wgpchvm by wanlige — VRAM 29.7GB, 986K context

Name: Mergekit Model Stock Wgpchvm
Author: wanlige

Mergekit Model Stock Wgpchvm is an open-source language model by wanlige. Features: 14b LLM, VRAM: 29.7GB, Context: 986K, Instruction-Based, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2403.19522 Autotrain compatible Base model:goekdeniz-guelmez/j... Base model:rombodawg/rombos-ll... Base model:suayptalha/lamarckv... Base model:tanliboy/lambda-qwe... Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/wanlige/mergekit-model_stock-wgpchvm

Mergekit Model Stock Wgpchvm Parameters and Internals

LLM Name	Mergekit Model Stock Wgpchvm
Repository 🤗	https://huggingface.co/wanlige/mergekit-model_stock-wgpchvm
Base Model(s)	tanliboy/lambda-qwen2.5-14b-dpo-test Mergekit Model Stock Ggfjmyf Lamarckvergence 14B rombodawg/Rombos-LLM-V2.6-Qwen-14b Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 tanliboy/lambda-qwen2.5-14b-dpo-test wanlige/mergekit-model_stock-ggfjmyf suayptalha/Lamarckvergence-14B rombodawg/Rombos-LLM-V2.6-Qwen-14b Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4
Merged Model	Yes
Model Size	14b
Required VRAM	29.7 GB
Updated	2025-02-23
Maintainer	wanlige
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 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 4.8 GB: 6-of-6
Model Architecture	Qwen2ForCausalLM
Context Length	1010000
Model Max Length	1010000
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Mergekit Model Stock Wgpchvm 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 Mergekit Model Stock Wgpchvm

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 wanlige/mergekit-model_stock-wgpchvm.