ArtificialGuyBR

Home / Blog / Fixing things

Llama 3.2 1B Synthia: Small Instruction Fine-Tune

ArtificialGuyBR's Llama 3.2 1B fine-tuned on Synthia-v1.5-I for better instruction following. Training details and how to run it.

1 sources cited Fixing things

On this page

  1. What This Model Does
  2. How It Was Trained
  3. How to Use It
  4. License
  5. Common Errors and Fixes
  6. FAQ
  7. Sources

Llama 3.2 1B Synthia: A Small Model Fine-Tuned for Instruction Following

Large language models grab the headlines, but the most practical models for local experimentation are the small ones. Llama 3.2 1B Synthia I Redmond by ArtificialGuyBR is a 1B-parameter instruction fine-tune of Meta's Llama 3.2 1B, trained on the Synthia-v1.5-I dataset with GPU support from RedmondAI. It targets the sweet spot between a tiny footprint and usable conversational ability.

What This Model Does

The base Llama 3.2 1B is a multilingual model from Meta. This version fine-tunes that base on Synthia-v1.5-I, an instruction dataset, with the aim of improving how well the model follows directions in conversational and task-following scenarios. The intended uses listed on the model card are instruction following, conversational AI applications, and NLP research and development. There are no trigger words or instance prompts here — unlike an image LoRA, you use it as a plain generative text model and prompt it directly.

For more of ArtificialGuyBR's models and projects, check the model hub or browse the LLM collection.

How It Was Trained

The model card publishes the full training recipe, which is useful if you want to reproduce or extend the fine-tune:

This is the pattern of small efficient fine-tunes: a lean dataset, short training, and a standard open-source stack. The RedmondAI GPU support is credited on the card as the compute behind the run.

How to Use It

The model is a text-generation pipeline model on Hugging Face. The quickest way to run it in Python:

from transformers import pipeline

gen = pipeline("text-generation", model="artificialguybr/LLAMA3.2-1B-Synthia-I-Redmond")
print(gen("Explain in one sentence what fine-tuning does.")[0]["generated_text"])

The model card does not publish specific inference settings, so start with the standard generation defaults for Llama 3.2 1B and tune temperature or top-p to taste. At 1B parameters it runs comfortably on CPU for short generations and easily on consumer GPUs. If you are working with other compact models, see the related small model fine-tunes.

License

This model is released under the Llama 3.2 Community License Agreement. Users must comply with all terms and conditions specified in that license, as stated on the model card.

Common Errors and Fixes

Error | Cause | Fix | Source

|---|---|---|---

Output is gibberish or off-topic | Model used without an instruct-style prompt | Prompt directly with a clear instruction; this is an instruct fine-tune, not a raw base model | Model card (intended use) Slow generation on GPU | 1B model run at full precision without acceleration | Use fp16 or quantisation via transformers/llama.cpp tooling | Model card (library: transformers) Download issues on Hugging Face | Large file sizes or rate limits | Use huggingface-cli download or retry during off-peak | Standard HF tooling

FAQ

Is this a vision or image model? No. It is a text-generation LLM in the LLM / Text Generation category.

Does it need trigger words? No. Instruction-tuned LLMs are prompted directly — there is no trigger word or instance prompt.

What languages does it support? The base model is multilingual: en, de, fr, it, pt, hi, es, and th.

Who provided the training compute? RedmondAI is credited on the model card for GPU support.

Sources