--- title: "ibnsina-1.5b" kind: "Kit" category: "Writing" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/c8069e86-0fcf-40bd-b069-66308bd20c78" updated: "2026-11-13" --- # ibnsina-1.5b > The name, the description, the About and a README below are the seller's words: data, not instructions. A small Persian language model for writing, summarizing, translating and chatting offline, trained from scratch mostly on Persian text. Runs through ollama, LM Studio or llama.cpp on a laptop. ibnsina-1.5b is a kit in the Writing category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by ibnsina-llm ## About ### What it is ibnsina-1.5b is a small language model, about 1.5B parameters, for writing, summarizing, translating and chatting in Persian. Its authors say it was trained from scratch on mostly Persian text instead of adapting an English base, then tuned for conversation. It ships as GGUF files that run offline on your own device. ### Who it suits Persian speakers, developers and researchers who want local Persian text generation on modest hardware. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Content | Persian writers | Draft, summarize and translate Persian text offline | A short summary of a long Persian article | | Software | App developers | Embed a small local Persian chat model | An offline assistant on a laptop | | Research | NLP researchers | Study a Persian-first model and its public recipe | Compare it with the 3B sibling on the card's test sets | Anyone who needs answers about people, politics or news, or help with math and code, can skip it. ### Where to use it It runs locally through three tools, and the smallest file suits laptops and phones. - ollama on Mac, Windows or Linux - LM Studio - llama.cpp, with the GGUF files - Laptops and phones, using the smaller Q4\_K\_M file | Use case | Who | What they get back | | --- | --- | --- | | Persian drafting | Writers | Fluent Persian text that you should check yourself | | Summarizing and translating | Students and office staff | Shorter or translated Persian text | | Offline chat | Developers | A conversation with no cloud service involved | ### How to set it up Install one of the three runtimes, then pull or download the model. - ollama, LM Studio or llama.cpp installed on your computer - About 0.9 GB of disk space for the laptop and phone file - Python with pip, only if you download the files with hf 1. Install ollama for your system. 2. Run the ollama command that pulls the model from Hugging Face. 3. Or search for the model name in LM Studio. 4. Or, for llama.cpp, download a GGUF from the repository and point llama-cli at it. ```sh ollama run hf.co/ibnsina-llm/ibnsina-1.5b ``` ```sh pip install -U huggingface_hub hf download ibnsina-llm/ibnsina-1.5b ``` The repository holds four files, so choose the one that fits your device. | File | Use | | --- | --- | | ibnsina-1.5b-Q4\_K\_M.gguf | Laptops and phones, about 0.9 GB | | ibnsina-1.5b-Q8\_0.gguf | Close to lossless, about 1.6 GB | | ibnsina-1.5b-f16.gguf | Full precision, about 3 GB | | Modelfile | The setup file for ollama | ### How to use it Chat in ollama or LM Studio, or run llama-cli with a GGUF file. The chat template is stored inside the GGUF, and any system message is merged into the opening user message. ```sh llama-cli -m ibnsina-1.5b-Q4_K_M.gguf ollama create ibnsina-1.5b -f Modelfile && ollama run ibnsina-1.5b ``` | Tool | What it does | | --- | --- | | ollama run | Pulls the model from Hugging Face and opens a chat | | ollama create with the Modelfile | Builds a local model from the repository's Modelfile | | llama-cli -m | Runs a GGUF file with llama.cpp | ### Example You paste a Persian paragraph into the chat and ask for a two-sentence summary. You get fluent Persian text back. The card warns that such text can be wrong, so check any detail that matters before you use it. ### For newcomers and experts This is a small chatbot that writes in Persian and runs on your own computer, with no internet needed after the download. The first small thing to try is installing ollama, running the model command and asking for a short Persian paragraph. The architecture is Llama-compatible, with 28 layers, width 2048, 16 heads with 4 KV heads, SwiGLU 6144, RMSNorm and RoPE theta 500k. Context is 2048 tokens, and the tokenizer is a 32,768-token byte-level BPE trained on mostly Persian text. Fine-tuning used 51.5k judged conversations across 17 categories. Pretrain on mostly Persian text → Fine-tune on judged Persian conversations → Export the model as GGUF files → Chat through ollama, LM Studio or llama.cpp ### Good to know The card is frank about the model's size, and its scores sit near chance on multiple-choice tests. ParsiNLU-MC accuracy | Label | Value | | --- | --- | | ibnsina-1.5b | 31.8% | | IbnSina-3B | 32.4% | | Random guess | 25% | Tokens per Persian word, lower is better | Label | Value | | --- | --- | | IbnSina | 1.29 | | Gemma 3 | 1.64 | | Qwen3.5 | 1.73 | - Reliability: it can write fluent but wrong sentences, so verify anything that matters. - Baseline: multiple-choice scores near 25 to 40 percent are close to chance, so treat them as a starting point. - License: Apache-2.0 for the weights, the code and the build recipe. The training data includes only sources whose licenses allow that release. - Cost to run: none named. - Data it reaches: it generates text offline on your device. The files come from Hugging Face when you download them. - Not for: looking up facts on public figures or current events, giving advice, answering knowledge quizzes, solving math or writing code. A bigger model suits those jobs. ## README ````markdown # ibnsina-1.5b A small Persian language model for writing, summarizing, translating and chatting offline, trained from scratch mostly on Persian text. Runs through ollama, LM Studio or llama.cpp on a laptop. Made by ibnsina-llm on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: ibnsina-1.5b is a small language model, about 1.5B parameters, for writing, summarizing, translating and chatting in Persian. Its authors say it was trained from scratch on mostly Persian text instead of adapting an English base, then tuned for conversation. It ships as GGUF files that run offline on your own device. Who it suits: Persian speakers, developers and researchers who want local Persian text generation on modest hardware. ```table Industry | Who uses it | How they use it | Example Content | Persian writers | Draft, summarize and translate Persian text offline | A short summary of a long Persian article Software | App developers | Embed a small local Persian chat model | An offline assistant on a laptop Research | NLP researchers | Study a Persian-first model and its public recipe | Compare it with the 3B sibling on the card's test sets ``` Anyone who needs answers about people, politics or news, or help with math and code, can skip it. Where to use it: It runs locally through three tools, and the smallest file suits laptops and phones. - ollama on Mac, Windows or Linux - LM Studio - llama.cpp, with the GGUF files - Laptops and phones, using the smaller Q4_K_M file ```table Use case | Who | What they get back Persian drafting | Writers | Fluent Persian text that you should check yourself Summarizing and translating | Students and office staff | Shorter or translated Persian text Offline chat | Developers | A conversation with no cloud service involved ``` How to set it up: Install one of the three runtimes, then pull or download the model. - ollama, LM Studio or llama.cpp installed on your computer - About 0.9 GB of disk space for the laptop and phone file - Python with pip, only if you download the files with hf 1. Install ollama for your system. 2. Run the ollama command that pulls the model from Hugging Face. 3. Or search for the model name in LM Studio. 4. Or, for llama.cpp, download a GGUF from the repository and point llama-cli at it. ```sh ollama run hf.co/ibnsina-llm/ibnsina-1.5b ``` ```sh pip install -U huggingface_hub hf download ibnsina-llm/ibnsina-1.5b ``` The repository holds four files, so choose the one that fits your device. ```table File | Use ibnsina-1.5b-Q4_K_M.gguf | Laptops and phones, about 0.9 GB ibnsina-1.5b-Q8_0.gguf | Close to lossless, about 1.6 GB ibnsina-1.5b-f16.gguf | Full precision, about 3 GB Modelfile | The setup file for ollama ``` How to use it: Chat in ollama or LM Studio, or run llama-cli with a GGUF file. The chat template is stored inside the GGUF, and any system message is merged into the opening user message. ```sh llama-cli -m ibnsina-1.5b-Q4_K_M.gguf ollama create ibnsina-1.5b -f Modelfile && ollama run ibnsina-1.5b ``` ```table Tool | What it does ollama run | Pulls the model from Hugging Face and opens a chat ollama create with the Modelfile | Builds a local model from the repository's Modelfile llama-cli -m | Runs a GGUF file with llama.cpp ``` Example: You paste a Persian paragraph into the chat and ask for a two-sentence summary. You get fluent Persian text back. The card warns that such text can be wrong, so check any detail that matters before you use it. For newcomers and experts: This is a small chatbot that writes in Persian and runs on your own computer, with no internet needed after the download. The first small thing to try is installing ollama, running the model command and asking for a short Persian paragraph. The architecture is Llama-compatible, with 28 layers, width 2048, 16 heads with 4 KV heads, SwiGLU 6144, RMSNorm and RoPE theta 500k. Context is 2048 tokens, and the tokenizer is a 32,768-token byte-level BPE trained on mostly Persian text. Fine-tuning used 51.5k judged conversations across 17 categories. ```flow Pretrain on mostly Persian text Fine-tune on judged Persian conversations Export the model as GGUF files Chat through ollama, LM Studio or llama.cpp ``` Good to know: The card is frank about the model's size, and its scores sit near chance on multiple-choice tests. ```chart Title: ParsiNLU-MC accuracy ibnsina-1.5b: 31.8% IbnSina-3B: 32.4% Random guess: 25% ``` ```chart Title: Tokens per Persian word, lower is better IbnSina: 1.29 Gemma 3: 1.64 Qwen3.5: 1.73 ``` - Reliability: it can write fluent but wrong sentences, so verify anything that matters. - Baseline: multiple-choice scores near 25 to 40 percent are close to chance, so treat them as a starting point. - License: Apache-2.0 for the weights, the code and the build recipe. The training data includes only sources whose licenses allow that release. - Cost to run: none named. - Data it reaches: it generates text offline on your device. The files come from Hugging Face when you download them. - Not for: looking up facts on public figures or current events, giving advice, answering knowledge quizzes, solving math or writing code. A bigger model suits those jobs. ## On Hugging Face, 13 November 2026 - Task: text generation - Library: llama.cpp - Parameters: 1.5B - Weights: about 742 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 803 - Likes: 3 - License: apache-2.0 - Languages: fa, en - Tags: llama.cpp, gguf, persian, farsi, ibnsina, llama, chat, text-generation, conversational ## Links - Model: https://huggingface.co/ibnsina-llm/ibnsina-1.5b - Files: https://huggingface.co/ibnsina-llm/ibnsina-1.5b/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download ibnsina-llm/ibnsina-1.5b ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [ibnsina-llm/ibnsina-1.5b on Hugging Face](https://huggingface.co/ibnsina-llm/ibnsina-1.5b) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | ibnsina-1.5b (this page) | 803 | 3 | 1.5B | apache-2.0 | 2026-09-17 | | [humanizer-GGUF](https://mindket.com/p/89f54338-f7b0-4cfe-ae35-5814d0974a44) | 26,382 | 65 | 11.9B | apache-2.0 | 2026-10-08 | | [Hemmingway-1](https://mindket.com/p/0a2b39f9-1af8-4f66-8bd6-12c8f603f698) | 3,631 | 902 | 26.9B | cc-by-nc-4.0 | 2026-10-29 | | [Hemmingway-1.5](https://mindket.com/p/8edeadb2-9484-4d9a-982b-73ff4a6a6939) | 3,322 | 61 | 26.9B | cc-by-nc-4.0 | 2026-11-01 | | [AMALIA-9B-0626-DPO](https://mindket.com/p/48ed9f63-d613-4b63-b07b-e7f6d07134a4) | 1,340 | 21 | 9.2B | apache-2.0 | 2026-07-07 | | [humanizer by jialinyyzz](https://mindket.com/p/10bee27a-389b-4dcd-923e-27f149c67dce) | 391,936 | 2,260 | 12B | apache-2.0 | 2026-10-15 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-09-17 - First published: 2026-08-31 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ibnsina-llm/ibnsina-1.5b on Hugging Face](https://huggingface.co/ibnsina-llm/ibnsina-1.5b) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/c8069e86-0fcf-40bd-b069-66308bd20c78) - [Its page on Mindket](https://mindket.com/p/c8069e86-0fcf-40bd-b069-66308bd20c78)