Instructions to use frett/chinese_extract_lert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_lert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_lert", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_lert") model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_lert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 234 Bytes
b0c20b6 | 1 2 3 4 5 6 7 8 9 | {
"epoch": 5.0,
"total_flos": 3.6156938713344e+16,
"train_loss": 0.40735532518307727,
"train_runtime": 4631.1638,
"train_samples": 27675,
"train_samples_per_second": 29.879,
"train_steps_per_second": 7.47
} |