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14ai/Polando-v1-1b-GGUF overview

Hey you The v2 version is avalibe Check out there : https://huggingface.co/14ai/Polando v2 1.5b GGUF Polando Polish Language Model 1B LoRA Adapter Welcome to t…

ggufbase_model:google/gemma-3-1b-itbase_model:quantized:google/gemma-3-1b-itlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~1.88 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Model Details

Model ID14ai/Polando-v1-1b-GGUF
Author14ai
Pipeline
Licenseapache-2.0
Base modelgoogle/gemma-3-1b-it
Last modified2026-07-03T14:52:41.000Z

Model README

---

license: apache-2.0

base_model:

  • google/gemma-3-1b-it

---

Hey you ! The v2 version is avalibe ! Check out there : https://huggingface.co/14ai/Polando-v2-1.5b-GGUF

Polando - Polish Language Model 1B (LoRA Adapter)

Welcome to the official repository of 14AI. This is a lightweight language model (LoRA adapter) optimized for text generation and conversation in the Polish language.

About the Project

The entire process of finetuning, configuration, and parameter debugging was conducted independently by a 14-year-old artificial intelligence enthusiast.

The model is based on the Google Gemma 3 1B architecture. Because of this baseline, the model may state that it was created by Google when asked about its authors. This is a behavior inherited from the base model, whereas its specific adaptation to the Polish language is the result of this finetuning project.

Model Characteristics and Limitations

Since the model contains only 1 billion parameters (1B), it has specific limitations and operational behaviors:

  • Language: The model was adapted primarily for communication in Polish.
  • Greeting Issues: The model may sometimes return empty responses or minimalist output when faced with basic Polish greetings like "witaj", "hej", or "halo". This is due to the probability distribution after the finetuning process.
  • Logic and Humor: The model performs well with basic mathematics, short responses, and can generate its own abstract humor.

Recommended Generation Parameters (Critical)

To prevent the model from hallucinating or returning empty outputs (especially during greetings), it is highly recommended to enforce the following generation parameters in your inference script:

  • max_new_tokens: 128 (or lower for shorter replies)
  • min_new_tokens: 5 (Critical parameter to prevent the model from generating an immediate End-of-String token)
  • do_sample: True
  • temperature: 0.1 (Low temperature ensures grammatical consistency and stability)
  • top_p: 0.8
  • repetition_penalty: 1.05

Thank you for your interest in this project.

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