What are the hardware requirements for YamshadowExperiment28 7B?

YamshadowExperiment28 7B 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 YamshadowExperiment28 7B and how large is it?

YamshadowExperiment28 7B is developed by automerger, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does YamshadowExperiment28 7B perform on standard benchmarks?

YamshadowExperiment28 7B has the following published scores: MMLU 64.38. Compare against reference models on this page or on the LLM Explorer leaderboards.

YamshadowExperiment28 7B by automerger — VRAM 14.4GB, 32K context

Name: YamshadowExperiment28 7B
Author: automerger

YamshadowExperiment28 7B is an open-source language model by automerger. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.21, Arc: 73.3, HellaSwag: 89.3, MMLU: 64.4, GSM8K: 70.5.

Merged Model Base model:yam-peleg/experimen... Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/automerger/YamshadowExperiment28-7B

YamshadowExperiment28 7B Parameters and Internals

Model Type

text generation

Use Cases

Applications:

research, commercial applications

Primary Use Cases:

chat-based applications

Limitations:

Overfitting to specific benchmarks.

Additional Notes

The model's excellent results on benchmark tests may be indicative of overfitting.

Training Details

Methodology:

Merge technique: SLERP between layers of two models

Context Length:

8000

Input Output

Input Format:

Alpaca chat template

Accepted Modalities:

text

Output Format:

text

Performance Tips:

The model can sometimes break and output a lot of "INST."

LLM Name	YamshadowExperiment28 7B
Repository 🤗	https://huggingface.co/automerger/YamshadowExperiment28-7B
Base Model(s)	YamShadow 7B Experiment28 7B automerger/YamShadow-7B yam-peleg/Experiment28-7B
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-02
Maintainer	automerger
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the YamshadowExperiment28 7B 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

Quantized Models of the YamshadowExperiment28 7B

Model	Likes	Downloads	VRAM
YamshadowExperiment28 7B GGUF	0	301	2 GB

Best Alternatives to YamshadowExperiment28 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than automerger/YamshadowExperiment28-7B.