Instructions to use frett/chinese_extract_longbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_longbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_longbert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
File size: 236 Bytes
9311223 | 1 2 3 4 5 6 7 8 9 | {
"epoch": 5.0,
"total_flos": 3.611513123226624e+16,
"train_loss": 3.3395631154378256,
"train_runtime": 2548.4435,
"train_samples": 27643,
"train_samples_per_second": 54.235,
"train_steps_per_second": 1.695
} |