Token Classification
GLiNER
PyTorch
English
thorntwig commited on
Commit
a7f9b10
1 Parent(s): c442469

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +1 -1
README.md CHANGED
@@ -11,7 +11,7 @@ This model is a fine-tune of [GLiNER](https://huggingface.co/urchade/gliner_larg
11
 
12
  ![results table](assets/zero-shot_18_table.png)
13
 
14
- The underlying dataset, [AskNews-NER-v0](https://huggingface.co/datasets/EmergentMethods/AskNews-NER-v0) was engineered with the objective of diversifying global perspectives by enforcing country/language/topic/temporal diversity. All data used to fine-tune this model was synthetically generated. WizardLM 13B v2.0 was used for translation/summarization of open-web news articles, while Llama3 70b instruct was used for entity extraction. Both the diversification and fine-tuning methods are presented in a [pre-print submitted to NeurIps2024](https://linktoarxiv.org).
15
 
16
  # Usage
17
 
 
11
 
12
  ![results table](assets/zero-shot_18_table.png)
13
 
14
+ The underlying dataset, [AskNews-NER-v0](https://huggingface.co/datasets/EmergentMethods/AskNews-NER-v0) was engineered with the objective of diversifying global perspectives by enforcing country/language/topic/temporal diversity. All data used to fine-tune this model was synthetically generated. WizardLM 13B v1.2 was used for translation/summarization of open-web news articles, while Llama3 70b instruct was used for entity extraction. Both the diversification and fine-tuning methods are presented in a [pre-print submitted to NeurIps2024](https://linktoarxiv.org).
15
 
16
  # Usage
17