What are the hardware requirements for OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA?

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA requires approximately 14.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA and how large is it?

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA is developed by sayhan, 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 OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA?

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA by sayhan — VRAM 14.4GB

Name: OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA
Author: sayhan

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA is an open-source language model by sayhan. Features: 7b LLM, VRAM: 14.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:teknium/o... Base model:teknium/openhermes-... Conversational Dataset:sayhan/strix-philosoph... En Endpoints compatible Gguf Lora Mistral Quantized Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA

OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA Parameters and Internals

Model Type

trl, text-generation-inference, unsloth, mistral, gguf

Additional Notes

LoRA rank: 8, LoRA alpha: 16, LoRA dropout: 0, Rank-stabilized LoRA: Yes, Number of epochs: 3, Learning rate: 1e-5, Batch size: 2, Gradient accumulation steps: 4, Weight decay: 0.01

Supported Languages

en (English)

Training Details

Data Sources:

sayhan/strix-philosophy-qa

Methodology:

LoRA (Low-Rank Adaptation)

LLM Name	OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA
Repository 🤗	https://huggingface.co/sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA
Base Model(s)	teknium/OpenHermes-2.5-Mistral-7B teknium/OpenHermes-2.5-Mistral-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-07-24
Maintainer	sayhan
Model Files	0.1 GB 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3 3.8 GB 14.5 GB 2.7 GB 3.5 GB 3.2 GB 4.1 GB 4.4 GB 4.1 GB 5.0 GB 5.1 GB 5.0 GB 5.9 GB 7.7 GB 14.5 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|v_proj\|down_proj\|o_proj\|q_proj\|up_proj\|gate_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	8

Rank the OpenHermes 2.5 Strix Philosophy Mistral 7B 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

Best Alternatives to OpenHermes 2.5 Strix Philosophy Mistral 7B LoRA

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ShoriRP V0.75d	0K / 0.2 GB	52	33
...wen Math 7b 24 1 100 1 Nonmath	0K / 15.2 GB	50	0
ReWiz 7B	0K / 14.5 GB	252	0
CleverBoi 7B V3	0K / 0.2 GB	193	0
Mistral 7B V0.1 Hitl	0K / 14.4 GB	14	0
...rendyol 7B Base V1 MtLoRA Entr	0K / 14.6 GB	25	0
Mistral Llm V4	0K / 14.4 GB	24	0
Gemma 7B English To Hinglish	0K / 17.1 GB	35	0
Gumzo Llama 00	0K / 0.3 GB	17	0
Legal Summarizer	0K / 14.4 GB	52	0

Note: green Score (e.g. "73.2") means that the model is better than sayhan/OpenHermes-2.5-Strix-Philosophy-Mistral-7B-LoRA.