What are the hardware requirements for Llamainstructbadendings?

Llamainstructbadendings requires approximately 2.5 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 Llamainstructbadendings and how large is it?

Llamainstructbadendings is developed by Elcaida, a model with 1.2b 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 Llamainstructbadendings?

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

Llamainstructbadendings by Elcaida — VRAM 2.5GB, 128K context

Name: Llamainstructbadendings
Author: Elcaida

Llamainstructbadendings is an open-source language model by Elcaida. Features: 1.2b LLM, VRAM: 2.5GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.17.

Base model:elcaida/llama-instr... Base model:finetune:elcaida/ll... Conversational En Endpoints compatible Llama Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Elcaida/llamainstructbadendings

Llamainstructbadendings Parameters and Internals

LLM Name	Llamainstructbadendings
Repository 🤗	https://huggingface.co/Elcaida/llamainstructbadendings
Base Model(s)	Llama Instructpretrained Elcaida/llama-instructpretrained
Model Size	1.2b
Required VRAM	2.5 GB
Updated	2026-08-08
Maintainer	Elcaida
Model Type	llama
Model Files	2.5 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.50.3
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llamainstructbadendings capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
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Data Analysis and Insight Generation
Text Generation
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Multi-Language Support and Translation

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Mazgu Llama V3 Merged	128K / 2.5 GB	301	0
Assn2 Sft Train5	128K / 2.5 GB	7	0
Zay Llama1b DPO Harmful PathD	128K / 2.5 GB	1	1
Akshar Nano V2	128K / 2.5 GB	15	0
Akshar Nano	128K / 2.5 GB	10	0
Second Tts Try	128K / 2.5 GB	39	0
...18 27e6 491c B3ab Ea03a5b93541	128K / 4.9 GB	10	0
...e9 9a4a 4ead 84f4 71761ee932ca	128K / 4.9 GB	6	0
SemAFacet SFT Merged 10K	128K / 4.9 GB	9	0
Llama Pubmed Example	128K / 2.5 GB	11	0

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