Writing Partner Mistral 7B By FPHam: Benchmarks, Features and Detailed Analysis. Insights on Writing Partner Mistral 7B.

Autotrain compatible Chatml Conversational En Endpoints compatible Finetuned Gpt4 Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/FPHam/Writing_Partner_Mistral_7B

Writing Partner Mistral 7B Benchmarks

ARC: 64.59 vs 96.7 (so35)^-33.2%

HellaSwag: 84.59 vs 95.3 (gpt4)^-11.2%

MMLU: 62.55 vs 88.3 (so35)^-29.2%

TruthfulQA: 48.55 vs 59 (gpt4)^-17.7%

WinoGrande: 76.87 vs 87.5 (gpt4)^-12.1%

GSM8K: 54.59 vs 96.4 (so35)^-43.4%

LLME Score: 0.1575

^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)

Writing Partner Mistral 7B (FPHam/Writing_Partner_Mistral_7B)

Writing Partner Mistral 7B Parameters and Internals

Model Type

Instruct, Finetune, ChatML, GPT-4

Use Cases

Areas:

Supportive Writing Tools

Applications:

Writing Assistance, Creative Writing, Story Development, Plot Formation, Dialogue Development

Primary Use Cases:

Writing Assistant for Fiction and Non-Fiction, Idea Generation, Character and Plot Development

Limitations:

Not intended to write content autonomously, meant for interaction and support only

Considerations:

The model should be used interactively and considerately, acknowledging the limitation of AI in comprehending nuanced artistic expression.

Additional Notes

Participation in the Open LLM Leaderboard to evaluate capabilities in various benchmarks.

Supported Languages

en (English)

Input Output

Input Format:

ChatML with user queries and assistant responses.

Accepted Modalities:

text

Output Format:

Textual responses in the form of writing advice, suggestions, and interactive dialogue.

Performance Tips:

Engage interactively and keep queries concise for optimal suggestions.

LLM Name	Writing Partner Mistral 7B
Repository 🤗	https://huggingface.co/FPHam/Writing_Partner_Mistral_7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2025-04-27
Maintainer	FPHam
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32002
Torch Data Type	float16

Quantized Models of the Writing Partner Mistral 7B

Model	Likes	Downloads	VRAM
...riting Partner Mistral 7B GGUF	12	2708	3 GB
...riting Partner Mistral 7B GPTQ	0	7	4 GB
Writing Partner Mistral 7B AWQ	0	5	4 GB

Best Alternatives to Writing Partner Mistral 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	2465	16
MegaBeam Mistral 7B 512K	512K / 14.4 GB	2136	50
SpydazWeb AI HumanAI RP	512K / 14.4 GB	2	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	1823	16
Hebrew Mistral 7B 200K	256K / 30 GB	11333	15
Astral 256K 7B V2	250K / 14.4 GB	21	0
Astral 256K 7B	250K / 14.4 GB	20	0

Note: green Score (e.g. "73.2") means that the model is better than FPHam/Writing_Partner_Mistral_7B.

Rank the Writing Partner Mistral 7B 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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