What are the hardware requirements for Llama Pubmed Example?

Llama Pubmed Example 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 Llama Pubmed Example and how large is it?

Llama Pubmed Example is developed by niznik-dev, 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 Llama Pubmed Example?

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

Llama Pubmed Example by niznik-dev — VRAM 2.5GB, 128K context

Name: Llama Pubmed Example
Author: niznik-dev

Llama Pubmed Example is an open-source language model by niznik-dev. Features: 1.2b LLM, VRAM: 2.5GB, Context: 128K, License: llama3.2, LLM Explorer Score: 0.17.

Conversational De En Endpoints compatible Es Facebook Fr Hi It Llama Llama-3 Meta Pt Pytorch Region:us Safetensors Sharded Tensorflow Th

Model Card on HF 🤗: https://huggingface.co/niznik-dev/llama-pubmed-example

Llama Pubmed Example Parameters and Internals

LLM Name	Llama Pubmed Example
Repository 🤗	https://huggingface.co/niznik-dev/llama-pubmed-example
Model Size	1.2b
Required VRAM	2.5 GB
Updated	2026-08-05
Maintainer	niznik-dev
Model Type	llama
Model Files	0.0 GB 2.5 GB: 1-of-1
Supported Languages	en de fr it pt hi es th
Model Architecture	LlamaForCausalLM
License	llama3.2
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.0.dev0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama Pubmed Example capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Mazgu Llama V3 Merged	128K / 2.5 GB	301	0
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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
Llamainstructbadendings	128K / 2.5 GB	13	0

Note: green Score (e.g. "73.2") means that the model is better than niznik-dev/llama-pubmed-example.