Token Classification
Transformers
Safetensors
English
deberta-v2
named-entity-recognition
person-names
historical-text
medieval
digital-humanities
prosopography
Instructions to use jmcewan3/LondonLB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmcewan3/LondonLB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jmcewan3/LondonLB")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jmcewan3/LondonLB") model = AutoModelForTokenClassification.from_pretrained("jmcewan3/LondonLB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from jmcewan3/LondonLB: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/jmcewan3/LondonLB/resolve/main/spm.model
- Command line
-
hf download hf://jmcewan3/LondonLB/spm.model
-
curl -L -o spm.model https://huggingface.co/jmcewan3/LondonLB/resolve/main/spm.model
2.46 MB
- Xet hash:
- ceef70ee5c068f2e8ec2ea787d1566d2f5846b612f0e0a3879edffa246dc91cf
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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