Instructions to use wt3639/NER_skill_extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wt3639/NER_skill_extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wt3639/NER_skill_extractor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wt3639/NER_skill_extractor") model = AutoModelForTokenClassification.from_pretrained("wt3639/NER_skill_extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from wt3639/NER_skill_extractor: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/wt3639/NER_skill_extractor/resolve/main/scheduler.pt
- Command line
-
hf download hf://wt3639/NER_skill_extractor/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/wt3639/NER_skill_extractor/resolve/main/scheduler.pt
1.06 kB
- Xet hash:
- 77daaa1fe92013f8de9d776de7a150ac2376b54b07b811a1ad00cd8fb4a9145d
- Size of remote file:
- 1.06 kB
- SHA256:
- f3cdfafc9d216f4d90f4030c693dc2b96ea4dbac55bced425e04c263f0e60a49
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