What are the hardware requirements for Danish Lm 400M Sft V31 Avg Top3?

Danish Lm 400M Sft V31 Avg Top3 requires approximately 1.7 GB of VRAM and supports a context window of 7K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Danish Lm 400M Sft V31 Avg Top3 and how large is it?

Danish Lm 400M Sft V31 Avg Top3 is developed by jensjepsen, a model with 400m 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 Danish Lm 400M Sft V31 Avg Top3?

Danish Lm 400M Sft V31 Avg Top3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Danish Lm 400M Sft V31 Avg Top3 by jensjepsen — VRAM 1.7GB, 7K context

Name: Danish Lm 400M Sft V31 Avg Top3
Author: jensjepsen

Danish Lm 400M Sft V31 Avg Top3 is an open-source language model by jensjepsen. Features: 400m LLM, VRAM: 1.7GB, Context: 7K, LLM Explorer Score: 0.29.

Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/jensjepsen/danish-lm-400m-sft-v31-avg-top3

Danish Lm 400M Sft V31 Avg Top3 Parameters and Internals

LLM Name	Danish Lm 400M Sft V31 Avg Top3
Repository 🤗	https://huggingface.co/jensjepsen/danish-lm-400m-sft-v31-avg-top3
Model Size	400m
Required VRAM	1.7 GB
Updated	2026-08-14
Maintainer	jensjepsen
Model Type	llama
Model Files	1.7 GB
Model Architecture	LlamaForCausalLM
Context Length	8048
Model Max Length	8048
Transformers Version	4.55.4
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	16007
Torch Data Type	float32

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Instruction Following and Task Automation
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Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
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Multi-Language Support and Translation

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