What are the hardware requirements for Replica IEPile?

Replica IEPile requires approximately 5.8 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 Replica IEPile and how large is it?

Replica IEPile is developed by necva, 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 Replica IEPile?

Replica IEPile is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Replica IEPile by necva — VRAM 5.8GB, 128K context

Name: Replica IEPile
Author: necva

Replica IEPile is an open-source language model by necva. Features: 8b LLM, VRAM: 5.8GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.23.

4-bit Base model:meta-llama/llama-3.... Base model:quantized:meta-llam... Bitsandbytes Dataset:zjunlp/iepile En Instruct Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/necva/replica-IEPile

Replica IEPile Parameters and Internals

LLM Name	Replica IEPile
Repository 🤗	https://huggingface.co/necva/replica-IEPile
Base Model(s)	meta-llama/Llama-3.1-8B-Instruct meta-llama/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	5.8 GB
Updated	2025-03-10
Maintainer	necva
Model Type	llama
Instruction-Based	Yes
Model Files	4.7 GB: 1-of-2 1.1 GB: 2-of-2
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.3
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float16

Rank the Replica IEPile 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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