What are the hardware requirements for Servile Harpsichord Cdpo?

Servile Harpsichord Cdpo requires approximately 14.4 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.

Who developed Servile Harpsichord Cdpo and how large is it?

Servile Harpsichord Cdpo is developed by chargoddard, a model with 7.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Servile Harpsichord Cdpo perform on standard benchmarks?

Servile Harpsichord Cdpo has the following published scores: MMLU 64.54. Compare against reference models on this page or on the LLM Explorer leaderboards.

Servile Harpsichord Cdpo by chargoddard — VRAM 14.4GB, 32K context

Name: Servile Harpsichord Cdpo
Author: chargoddard

Servile Harpsichord Cdpo is an open-source language model by chargoddard. Features: 7.2b LLM, VRAM: 14.4GB, Context: 32K, License: cc-by-nc-4.0, LLM Explorer Score: 0.11, Arc: 67.3, HellaSwag: 85.2, MMLU: 64.5, GSM8K: 57.1.

Dataset:allenai/ultrafeedback ... Dataset:chargoddard/rpguild Dataset:intel/orca dpo pairs Dataset:lemonilia/limarp Dataset:openai/summarize from ... Dataset:pankajmathur/orca mini... Dataset:pku-alignment/pku-safe... Dataset:pygmalionai/pippa Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/chargoddard/servile-harpsichord-cdpo

Servile Harpsichord Cdpo Parameters and Internals

Training Details

Data Sources:

pankajmathur/orca_mini_v1_dataset, openai/summarize_from_feedback, PygmalionAI/PIPPA, chargoddard/rpguild, lemonilia/LimaRP, PKU-Alignment/PKU-SafeRLHF, Intel/orca_dpo_pairs, allenai/ultrafeedback_binarized_cleaned

Methodology:

Trained on a different random sampling of the same datasets used by loyal-piano-m7, followed by cDPO on a blend of RLHF datasets

Input Output

Input Format:

Alpaca prompt format

LLM Name	Servile Harpsichord Cdpo
Repository 🤗	https://huggingface.co/chargoddard/servile-harpsichord-cdpo
Model Size	7.2b
Required VRAM	14.4 GB
Updated	2026-08-08
Maintainer	chargoddard
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3 0.0 GB
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Servile Harpsichord Cdpo 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 chargoddard/servile-harpsichord-cdpo.