FuseChat 7B VaRM By FuseAI: Benchmarks, Features and Detailed Analysis. Insights on FuseChat 7B VaRM.

Arxiv:2402.16107 Autotrain compatible Base model:finetune:openchat/o... Base model:openchat/openchat 3... Conversational Dataset:fuseai/fusechat-mixtur... En Endpoints compatible Fusechat Mistral Mixtral Model-fusion Model-index Pytorch Region:us Safetensors Solar

Model Card on HF 🤗: https://huggingface.co/FuseAI/FuseChat-7B-VaRM

FuseChat 7B VaRM Benchmarks

ARC: 62.88 vs 96.7 (so35)^-35%

HellaSwag: 84.25 vs 95.3 (gpt4)^-11.6%

MMLU: 63.71 vs 88.3 (so35)^-27.8%

TruthfulQA: 45.67 vs 59 (gpt4)^-22.6%

WinoGrande: 79.16 vs 87.5 (gpt4)^-9.5%

GSM8K: 63.46 vs 96.4 (so35)^-34.2%

LLME Score: 0.19805

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

FuseChat 7B VaRM (FuseAI/FuseChat-7B-VaRM)

FuseChat 7B VaRM Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

chat applications, text generation

Applications:

commercial applications, research

Primary Use Cases:

multi-modal chat, roleplay, reasoning, math, coding, writing

Additional Notes

Includes techniques from mixtral and solar to enhance performance.

Supported Languages

en (fluent)

Training Details

Data Sources:

FuseAI/FuseChat-Mixture, human-written, model-generated

Methodology:

Pairwise knowledge fusion and model merging

Context Length:

2048

Model Architecture:

Fuse and merge strategy with multiple source LLMs

Input Output

Input Format:

Text input with proper prompts

Accepted Modalities:

text

Output Format:

Generated text

Performance Tips:

Ensure GPU availability for better performance

Release Notes

Version:

7B-VaRM

Notes:

Fusion of three chat LLMs with diverse architectures and scales. Achieves high performance on various benchmarks.

LLM Name	FuseChat 7B VaRM
Repository 🤗	https://huggingface.co/FuseAI/FuseChat-7B-VaRM
Base Model(s)	openchat/openchat_3.5 openchat/openchat_3.5
Model Size	7b
Required VRAM	14.5 GB
Updated	2025-02-22
Maintainer	FuseAI
Model Type	mistral
Model Files	14.5 GB 14.5 GB
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.36.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32002
Torch Data Type	bfloat16

Quantized Models of the FuseChat 7B VaRM

Model	Likes	Downloads	VRAM
FuseChat 7B VaRM AWQ	1	7	4 GB

Best Alternatives to FuseChat 7B VaRM

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	4620	11
MegaBeam Mistral 7B 512K	512K / 14.4 GB	5681	50
SpydazWeb AI HumanAI RP	512K / 14.4 GB	12	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	5633	16
Hebrew Mistral 7B 200K	256K / 30 GB	14619	15
Astral 256K 7B V2	250K / 14.4 GB	7	0
Astral 256K 7B	250K / 14.4 GB	5	0
Test001	128K / 14.5 GB	9	0

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

Rank the FuseChat 7B VaRM Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Original data from HuggingFace, OpenCompass and various public git repos.

Release v20241227

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