What are the hardware requirements for Nemo Merge DPO V1ori?

Nemo Merge DPO V1ori requires approximately 24.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemo Merge DPO V1ori and how large is it?

Nemo Merge DPO V1ori is developed by NischayDnk, a model with 12.2b 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 Nemo Merge DPO V1ori?

Nemo Merge DPO V1ori is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemo Merge DPO V1ori by NischayDnk — VRAM 24.5GB, 128K context

Name: Nemo Merge DPO V1ori
Author: NischayDnk

Nemo Merge DPO V1ori is an open-source language model by NischayDnk. Features: 12.2b LLM, VRAM: 24.5GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.16.

Merged Model Autotrain compatible Base model:mistralai/mistral-n... Base model:nischaydnk/mistraln... Conversational Endpoints compatible Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/NischayDnk/Nemo-Merge-DPO-v1ori

Nemo Merge DPO V1ori Parameters and Internals

LLM Name	Nemo Merge DPO V1ori
Repository 🤗	https://huggingface.co/NischayDnk/Nemo-Merge-DPO-v1ori
Base Model(s)	Mistral Nemo Instruct 2407 Mistralnemo DPO V1 Rp mistralai/Mistral-Nemo-Instruct-2407 NischayDnk/Mistralnemo-dpo-v1-rp
Merged Model	Yes
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2025-03-14
Maintainer	NischayDnk
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Model Architecture	MistralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Nemo Merge DPO V1ori 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 Nemo Merge DPO V1ori

Best Alternatives	Context / RAM	Downloads	Likes
...istral Nemo Instruct 2407 MPOA	1000K / 24.5 GB	37	3
...ish Mistral Nemo Instruct 2407	1000K / 24.5 GB	77	2
Mistral Nemo Kurdish	1000K / 24.5 GB	37	3
Violet Twilight V0.2	1000K / 24.5 GB	66	49
Kalypso	1000K / 24.5 GB	45	24
Crimson Dawn V0.2	1000K / 24.5 GB	17	13
Azure Dusk V0.2	1000K / 24.5 GB	43	10
...al Nemo Japanese Instruct 2408	1000K / 24.5 GB	2358	49
Mistral Nemo Instruct 2407 FP8	1000K / 13.6 GB	4691	19
Educa Ai Nemo Sft	1000K / 49.3 GB	13	4

Note: green Score (e.g. "73.2") means that the model is better than NischayDnk/Nemo-Merge-DPO-v1ori.