Instructions to use sxandie/autotrain-re_syn_cleanedtext_bert-55272128958 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sxandie/autotrain-re_syn_cleanedtext_bert-55272128958 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sxandie/autotrain-re_syn_cleanedtext_bert-55272128958")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sxandie/autotrain-re_syn_cleanedtext_bert-55272128958") model = AutoModelForTokenClassification.from_pretrained("sxandie/autotrain-re_syn_cleanedtext_bert-55272128958", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5153660bbe2fdf2fa550627c7470185e438f21775cce899e43202af733f16a06
- Size of remote file:
- 709 MB
- SHA256:
- 36c2331254228502c9709dbde12e82f21e6ea9b46613752192e7a39187a5df96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.