Text Generation
Turkish
llama
causal-lm
slm
experimental
turkish
tr-llm
AhiskaAI

AhıskaAI-110M-Experimental-v0.1

AhıskaAI-110M-Experimental-v0.1 is a 110M parameter Small Language Model (SLM) trained from scratch as part of the experimental release series by AhıskaAI. This series focuses on evaluating early-stage convergence and reasoning behavior on synthetic Turkish datasets (covering math, web content, and narrative stories).

Experimental Setup & Scope

  • Objective: Test synthetic data density (Math + Web + Stories) and sequence modeling performance on a compact 110M Llama architecture.
  • Training Epochs: Pre-trained for 0.3 epochs across a ~3.5 GB synthetic Turkish corpus.
  • Context Length: 1024 tokens.

Model Details

  • Architecture: LlamaForCausalLM (Standard MHA)
  • Parameters: ~110M
  • Hidden Size: 768
  • Intermediate Size: 2048
  • Attention Heads: 12 (Query) / 12 (Key/Value)
  • Layers: 12
  • Context Length: 1024 tokens
  • Vocabulary Size: 32,000
  • Precision: float32 / float16

Pre-training Dataset Mixture

The model was pre-trained on a synthetic Turkish corpus (~3.5 GB total):

Data Source Approx. Size Primary Focus Link
BILGEM AI Synthetic Web ~2.0 GB General Web, Knowledge & Grammar BILGEM-AI/BILGE-Synthetic-Web
BILGEM AI Synthetic Math ~750 MB Mathematical Reasoning & Logic BILGEM-AI/BILGE-Synthetic-Math
BILGEM AI Synthetic Stories ~750 MB Narrative Flow & Text Generation BILGEM-AI/BILGE-Synthetic-Stories

Usage

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "AhıskaAI/AhıskaAI-110M-Experimental-v0.1"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
    device_map="auto"
)

prompt = "Bir zamanlar uzak bir ülkede"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=100,
    temperature=0.7,
    top_p=0.9,
    do_sample=True
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

About AhıskaAI

AhıskaAI is an independent initiative dedicated to developing efficient, high-performance Small Language Models (SLMs) tailored for the Turkish language ecosystem.

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Datasets used to train AhiskaAI/AhiskaAI-110M-Experimental-v0.1-Base

Collection including AhiskaAI/AhiskaAI-110M-Experimental-v0.1-Base