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| Version | Base Model | URL | Training |
|---|---|---|---|
| V1 0.5B | Qwen 2 0.5B Instruct | fp16 | Epoch = 1, Batch = 16*8, lr = 5e-5, linear schedule |
| V1 1.5B | Qwen 2 1.5B Instruct | fp16 | Epoch = 1, Batch = 16*8, lr = 5e-5, linear schedule |
| V1 9B | Gemma 2 9B Instruct | fp16/4bit | Batch size = 16*8, lr = 4e-5, linear schedule |
from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
tokenizer = AutoTokenizer.from_pretrained("afrizalha/Bakpia-V1-0.5B-Javanese")
model = AutoModelForCausalLM.from_pretrained("afrizalha/Bakpia-V1-0.5B-Javanese")
model.to("cuda")
template = """<|im_start|>system
<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
"""
input = template.format(prompt="Kados pundi kulo saged nyinaoni Basa Jawa kanthi sae?"
input = tokenizer([input], return_tensors = "pt").to("cuda")
outputs = model.generate(**input, max_new_tokens = 1024, streamer= TextStreamer(tokenizer), temperature=.5, use_cache=True, do_sample=True)