Instructions to use Curiousfox/mT5_tai-lo_to_chinese_LoRA_ver1.0.k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Curiousfox/mT5_tai-lo_to_chinese_LoRA_ver1.0.k with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-base") model = PeftModel.from_pretrained(base_model, "Curiousfox/mT5_tai-lo_to_chinese_LoRA_ver1.0.k") - Transformers
How to use Curiousfox/mT5_tai-lo_to_chinese_LoRA_ver1.0.k with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Curiousfox/mT5_tai-lo_to_chinese_LoRA_ver1.0.k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 276 Bytes
fe699bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"backend": "tokenizers",
"eos_token": "</s>",
"extra_ids": 0,
"extra_special_tokens": [],
"is_local": false,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"tokenizer_class": "T5Tokenizer",
"unk_id": 2,
"unk_token": "<unk>"
}
|