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tiyat_2_alpha
tachiwin/tiyat_2_alpha
tiyat_2_alpha is a text generation model from tachiwin. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
- Tokenizer: tachiwin/tokenizer64k - Vocabulary Size: 64,000 - Max Sequence Length: 918 - Embedding Dimension: 256 - Number of Layers: 4 - Number of Heads: 4 - Feed-Forward Dimension: 1024 - Total Parameters: ~19.8M
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At a glance
- Task
- Text Generation
- License
- apache-2.0
- Model type
- gpt2
- Access
- Public
- Created
- Sep 2, 2026
- Updated
- Sep 2, 2026
- SHA
- ae88c5d7
Base models
Model card
From the Hugging Face model README
Tiyat Alpha - Custom LLM
Model Details
- Tokenizer: tachiwin/tokenizer_64k
- Vocabulary Size: 64,000
- Max Sequence Length: 918
- Embedding Dimension: 256
- Number of Layers: 4
- Number of Heads: 4
- Feed-Forward Dimension: 1024
- Total Parameters: ~19.8M
Training Data
- Dataset: tachiwin/tiyat-ground-pretrain-m1024
Training Configuration
- Batch Size: 16
- Learning Rate: 0.0005
- Weight Decay: 0.01
- Gradient Clip: 1.0
- Warmup Ratio: 0.1
- Dropout Rate: 0.1
- Total Steps: 35418
- Final Loss: 4.8666
Usage
from transformers import AutoTokenizer, FlaxAutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("tachiwin/tiyat_2_alpha")
model = FlaxAutoModelForCausalLM.from_pretrained("tachiwin/tiyat_2_alpha")
# Generate text
inputs = tokenizer("Your prompt here", return_tensors="np")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0]))
- Task
- Text Generation
- Type
- gpt2
- License
- apache-2.0
- Languages
- multilingual
- Created
- Sep 2, 2026
- Updated
- Sep 2, 2026