metadata

library_name: transformers
license: apache-2.0
datasets:
  - oscar-corpus/OSCAR-2301
language:
  - th
base_model:
  - EleutherAI/pythia-2.8b-deduped
pipeline_tag: text-generation

This model is currently in the training stage and may produce hallucinations

Example Use

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Naphon/pythia-2.8b-thai-base-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto",
    trust_remote_code=True
)

text = "รองศาสตราจารย์ ดร.สุวิทย์ แซ่เตีย อธิการบดีมหาวิทยาลัยเทคโนโลยีพระจอมเกล้าธนบุรี"
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=50, do_sample=True, temperature=0.9)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))