What are the hardware requirements for DMoE 8B Pretrain 0520 Iter134999?

DMoE 8B Pretrain 0520 Iter134999 requires approximately 18 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DMoE 8B Pretrain 0520 Iter134999 and how large is it?

DMoE 8B Pretrain 0520 Iter134999 is developed by geniacllm, a model with 8b 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 DMoE 8B Pretrain 0520 Iter134999?

DMoE 8B Pretrain 0520 Iter134999 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DMoE 8B Pretrain 0520 Iter134999 by geniacllm — VRAM 18GB, 2K context

Name: DMoE 8B Pretrain 0520 Iter134999
Author: geniacllm

DMoE 8B Pretrain 0520 Iter134999 is an open-source language model by geniacllm. Features: 8b LLM, VRAM: 18GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.12.

Autotrain compatible Endpoints compatible Mixtral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/geniacllm/dMoE_8B_pretrain_0520_iter134999

DMoE 8B Pretrain 0520 Iter134999 Parameters and Internals

LLM Name	DMoE 8B Pretrain 0520 Iter134999
Repository 🤗	https://huggingface.co/geniacllm/dMoE_8B_pretrain_0520_iter134999
Model Size	8b
Required VRAM	18 GB
Updated	2024-08-15
Maintainer	geniacllm
Model Type	mixtral
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 3.0 GB: 4-of-4
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.41.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	56320
Torch Data Type	bfloat16

Rank the DMoE 8B Pretrain 0520 Iter134999 capabilities

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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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Lamma3merge3 15B MoE	8K / 27.5 GB	11	1
Lamma3merge2 15B MoE	8K / 27.5 GB	10	0
Llama3merge7 15B MoE	8K / 27.5 GB	7	0
Mergkit 1	8K / 22.6 GB	5	0
Llama 3 8B Shisa 2x8B	8K / 7.4 GB	3	2
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...8B Finetune All V6 Epoch2 V0.1	2K / 18 GB	9	1
...Storm V1.15 4x8B B 8 0bpw EXL2	8K / 25.2 GB	6	0
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Note: green Score (e.g. "73.2") means that the model is better than geniacllm/dMoE_8B_pretrain_0520_iter134999.