What are the hardware requirements for ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3?

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 requires approximately 1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 and how large is it?

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 is developed by matouLeLoup, a model with 0.5b 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 ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3?

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 by matouLeLoup — VRAM 1GB, 128K context

Name: ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3
Author: matouLeLoup

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 is an open-source language model by matouLeLoup. Features: 0.5b LLM, VRAM: 1GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.17.

Autotrain compatible Dataset:allenai/qasc En Endpoints compatible Enhanced-ensemble Instruct Multi-source Musr Qwen Qwen2 Reasoning Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/matouLeLoup/ECE-PRYMMAL-0.5B-FT-EnhancedMUSREnsembleV3

ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 Parameters and Internals

LLM Name	ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3
Repository 🤗	https://huggingface.co/matouLeLoup/ECE-PRYMMAL-0.5B-FT-EnhancedMUSREnsembleV3
Model Size	0.5b
Required VRAM	1 GB
Updated	2024-11-18
Maintainer	matouLeLoup
Model Type	qwen2
Model Files	1.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3 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

Best Alternatives to ECE PRYMMAL 0.5B FT EnhancedMUSREnsembleV3

Best Alternatives	Context / RAM	Downloads	Likes
Reader Lm 0.5B	250K / 1 GB	188	150
Qwen2 0.5B	128K / 1 GB	1216780	169
Qwen2 0.5B Finetune Exp 1	128K / 1 GB	15	0
....5B FT V4 MUSR ENSEMBLE Mathis	128K / 2 GB	30	1
...0.5B FT MUSR ENSEMBLE V2Mathis	128K / 1 GB	25	0
...PRYMMAL 0.5B FT V4 MUSR Mathis	128K / 1 GB	62	1
Qwen2 0.5B Stf Imdb	128K / 1 GB	7	0
ECE PRYMMAL 0.5B FT V3 MUSR	128K / 2 GB	17	0
ECE PRYMMAL 0.5B FT V4 MUSR	128K / 2 GB	10	0
...44 45ee 44f3 934d Ddc8b6e082f1	128K / 1 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than matouLeLoup/ECE-PRYMMAL-0.5B-FT-EnhancedMUSREnsembleV3.