What are the hardware requirements for Llama2 MedTuned 7B?

Llama2 MedTuned 7B requires approximately 13.5 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama2 MedTuned 7B and how large is it?

Llama2 MedTuned 7B is developed by nlpie, a model with 7b 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 Llama2 MedTuned 7B?

Llama2 MedTuned 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama2 MedTuned 7B by nlpie — VRAM 13.5GB, 4K context

Name: Llama2 MedTuned 7B
Author: nlpie

Llama2 MedTuned 7B is an open-source language model by nlpie. Features: 7b LLM, VRAM: 13.5GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.1.

Biomedical Clinical Deploy:azure Endpoints compatible Llama Medical Oxford-legacy Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/nlpie/Llama2-MedTuned-7b

Llama2 MedTuned 7B Parameters and Internals

Model Type

biomedical, clinical, medical

Use Cases

Areas:

research

Applications:

biomedical language processing

Primary Use Cases:

Named Entity Recognition (NER), Relation Extraction (RE), Medical Natural Language Inference (NLI)

LLM Name	Llama2 MedTuned 7B
Repository 🤗	https://huggingface.co/nlpie/Llama2-MedTuned-7b
Model Size	7b
Required VRAM	13.5 GB
Updated	2026-08-04
Maintainer	nlpie
Model Type	llama
Model Files	10.0 GB: 1-of-2 3.5 GB: 2-of-2
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.34.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Llama2 MedTuned 7B 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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162	1024K / 16.1 GB	60
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A2.4	1024K / 16.1 GB	12
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Note: green Score (e.g. "73.2") means that the model is better than nlpie/Llama2-MedTuned-7b.