What are the hardware requirements for Moss Moon 003 Sft Int4 Fix Autotune?

Moss Moon 003 Sft Int4 Fix Autotune requires approximately 10.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Moss Moon 003 Sft Int4 Fix Autotune and how large is it?

Moss Moon 003 Sft Int4 Fix Autotune is developed by DotIN13. 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 Moss Moon 003 Sft Int4 Fix Autotune?

Moss Moon 003 Sft Int4 Fix Autotune is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Moss Moon 003 Sft Int4 Fix Autotune by DotIN13 — VRAM 10.8GB

Name: Moss Moon 003 Sft Int4 Fix Autotune
Author: DotIN13

Moss Moon 003 Sft Int4 Fix Autotune is an open-source language model by DotIN13. Features: LLM, VRAM: 10.8GB, License: agpl-3.0, LLM Explorer Score: 0.07.

Arxiv:2203.13474 Custom code Dataset:fnlp/moss-002-sft-data En Moss Pytorch Region:us Zh

Model Card on HF 🤗: https://huggingface.co/DotIN13/moss-moon-003-sft-int4-fix-autotune

Moss Moon 003 Sft Int4 Fix Autotune Benchmarks

LLME Score: 0.07096

^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)

Moss Moon 003 Sft Int4 Fix Autotune (DotIN13/moss-moon-003-sft-int4-fix-autotune)

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Moss Moon 003 Sft Int4 Fix Autotune Parameters and Internals

Model Type

Conversational language model

Use Cases

Areas:

Research, Commercial applications

Applications:

Multi-turn dialogues, Plugin-augmented functions

Primary Use Cases:

Conversational AI, Language-based tasks

Limitations:

Can generate incorrect, misleading, or biased information.

Considerations:

Carefully check contents generated by the model before use.

Additional Notes

Possible improvement plans involve reasoning, truthfulness, safety, multi-modality, and personalization.

Supported Languages

en (English), zh (Chinese)

Training Details

Data Sources:

The PILE, BigQuery, BigPython, Private Chinese corpus

Data Volume:

~700B tokens

Methodology:

Supervised Fine-tuning, Preference-aware training

Context Length:

2048

Training Time:

Not specified

Hardware Used:

2 NVIDIA 3090 GPUs with FP16 precision

Model Architecture:

Initialized with CodeGen and fine-tuned on multi-turn plugin-augmented conversational data.

Responsible Ai Considerations

Fairness:

Not specified

Transparency:

Not specified

Accountability:

Unspecified

Mitigation Strategies:

Not specified

Input Output

Input Format:

text input

Accepted Modalities:

text

Output Format:

text output

Performance Tips:

Use FP16 precision for enhanced performance on A100 or similar GPUs.

LLM Name	Moss Moon 003 Sft Int4 Fix Autotune
Repository 🤗	https://huggingface.co/DotIN13/moss-moon-003-sft-int4-fix-autotune
Required VRAM	10.8 GB
Updated	2026-04-26
Maintainer	DotIN13
Model Type	moss
Model Files	10.8 GB
Supported Languages	en zh
Model Architecture	MossForCausalLM
License	agpl-3.0
Model Max Length	2048
Transformers Version	4.25.1
Tokenizer Class	GPT2Tokenizer
Beginning of Sentence Token	<\|endoftext\|>
End of Sentence Token	<eom>
Unk Token	<\|endoftext\|>
Vocabulary Size	107008
Torch Data Type	float16
Activation Function	gelu_new
Errors	replace

Best Alternatives to Moss Moon 003 Sft Int4 Fix Autotune

Best Alternatives	Context / RAM	Downloads	Likes
Moss Moon 003 Base	0K / 33.5 GB	1117	132
Moss Moon 003 Sft	0K / 33.5 GB	852	128
Moss Moon 003 Sft Plugin	0K / 33.5 GB	978	71
Moss Moon 003 Base	0K / 33.5 GB	247	131
Moss Moon 003 Sft	0K / 33.5 GB	21	127
Moss Moon 003 Sft Int8	0K / 18.5 GB	209	14
Moss Moon 003 Sft Plugin	0K / 33.5 GB	7	69
Moss Moon 003 Sft Plugin Int4	0K / 10.8 GB	168	18
Moss Moon 003 Sft Int4	0K / 10.8 GB	41	41
Moss Moon 003 Sft Int4	0K / 10.8 GB	42	40

Note: green Score (e.g. "73.2") means that the model is better than DotIN13/moss-moon-003-sft-int4-fix-autotune.

Rank the Moss Moon 003 Sft Int4 Fix Autotune 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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Release v20260328a

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Moss Moon 003 Sft Int4 Fix Autotune by DotIN13

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Moss Moon 003 Sft Int4 Fix Autotune Benchmarks

Moss Moon 003 Sft Int4 Fix Autotune Parameters and Internals

Best Alternatives to Moss Moon 003 Sft Int4 Fix Autotune

Rank the Moss Moon 003 Sft Int4 Fix Autotune Capabilities

What open-source LLMs or SLMs are you in search of? 54028 in total.