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DictaLM 3.0 here.1from transformers import pipeline
2import torch
3
4# This loads the model onto the GPU in bfloat16 precision
5model = pipeline('text-generation', 'dicta-il/DictaLM-3.0-24B-Base', torch_dtype=torch.bfloat16, device_map='auto')
6
7# Sample few shot examples
8prompt = """
9עבר: הלכתי
10עתיד: אלך
11
12עבר: שמרתי
13עתיד: אשמור
14
15עבר: שמעתי
16עתיד: אשמע
17
18עבר: הבנתי
19עתיד:
20"""
21
22print(model(prompt.strip(), do_sample=False, max_new_tokens=8, stop_sequence='\n'))
23# [{'generated_text': 'עבר: הלכתי\nעתיד: אלך\n\nעבר: שמרתי\nעתיד: אשמור\n\nעבר: שמעתי\nעתיד: אשמע\n\nעבר: הבנתי\nעתיד: אבין\n\nעבר: קרא'}]vllm serve dicta-il/DictaLM-3.0-24B-Base If you run out of memory, you can try limiting the context window by setting--max-model-len 8192
1@article{Shmidman2025DictaLM3,
2 title={{Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs}},
3 author={Shaltiel Shmidman and Avi Shmidman and Amir DN Cohen and Moshe Koppel},
4 year={2025},
5 publisher={{DICTA / Jerusalem, Israel}},
6 note={https://www.dicta.org.il/publications/DictaLM_3_0___Techincal_Report.pdf}
7}