What are the hardware requirements for Prodigy Sm Base V0.1?

Prodigy Sm Base V0.1 requires approximately 14.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Prodigy Sm Base V0.1 and how large is it?

Prodigy Sm Base V0.1 is developed by iskonai, 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 Prodigy Sm Base V0.1?

Prodigy Sm Base V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Prodigy Sm Base V0.1 by iskonai — VRAM 14.5GB, 32K context

Name: Prodigy Sm Base V0.1
Author: iskonai

Prodigy Sm Base V0.1 is an open-source language model by iskonai. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.12.

Arxiv:2309.09530 Arxiv:2403.19522 Bs En Endpoints compatible Hr Mistral Region:us Safetensors Sharded Sr Tensorflow

Model Card on HF 🤗: https://huggingface.co/iskonai/prodigy-sm-base-v0.1

Prodigy Sm Base V0.1 Parameters and Internals

Additional Notes

This model serves as a base model with potential for further pre-training on Serbian language or tuning for specific tasks.

Supported Languages

en (English), sr (Serbian), hr (Croatian), bs (Bosnian)

Training Details

Data Sources:

Synthetic data, Human-curated data, CC Web data

Methodology:

Continued pre-training using a compact set of synthetic and human-curated data along with CC Web data

LLM Name	Prodigy Sm Base V0.1
Repository 🤗	https://huggingface.co/iskonai/prodigy-sm-base-v0.1
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-06-08
Maintainer	iskonai
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.6 GB: 2-of-2
Supported Languages	en sr hr bs
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Prodigy Sm Base V0.1 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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Note: green Score (e.g. "73.2") means that the model is better than iskonai/prodigy-sm-base-v0.1.