Instructions to use Ezekiel999/AksaraLLM-20B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ezekiel999/AksaraLLM-20B-Instruct with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ezekiel999/AksaraLLM-20B-Instruct", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Ezekiel999/AksaraLLM-20B-Instruct (smoke-test checkpoint)
This is NOT the production 20B model. It is a randomly-initialized
tiny preset (2 layers, 64-dim, vocab 256) pushed from a Devin
scaffolding session to validate the aksaraLLMModel.save_pretrained โ
HF โ aksaraLLMModel.from_pretrained round-trip.
The real 20B model (42 layers, 6144-dim, vocab 131 072) must be trained
from random initialisation on a TPU v5p pod using
aksara-train/scripts/train_20b_pretrain.py.
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