Add library_name to metadata
#1
by
nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,16 +1,17 @@
|
|
| 1 |
---
|
| 2 |
-
|
|
|
|
| 3 |
datasets:
|
| 4 |
- prachuryyaIITG/CLASSER
|
| 5 |
language:
|
| 6 |
- ne
|
|
|
|
| 7 |
metrics:
|
| 8 |
- f1
|
| 9 |
- precision
|
| 10 |
- recall
|
| 11 |
-
base_model:
|
| 12 |
-
- google/muril-large-cased
|
| 13 |
pipeline_tag: token-classification
|
|
|
|
| 14 |
tags:
|
| 15 |
- NER
|
| 16 |
- Named_Entity_Recognition
|
|
@@ -19,6 +20,8 @@ pretty_name: CLASSER Nepali MuRIL
|
|
| 19 |
|
| 20 |
**MuRIL is fine-tuned on Nepali [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) dataset for Fine-grained Named Entity Recognition.**
|
| 21 |
|
|
|
|
|
|
|
| 22 |
The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
|
| 23 |
|
| 24 |
* Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
|
|
@@ -110,4 +113,5 @@ If you use this model, please cite the following papers:
|
|
| 110 |
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
|
| 111 |
pages={2027--2051},
|
| 112 |
year={2023}
|
| 113 |
-
}
|
|
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model:
|
| 3 |
+
- google/muril-large-cased
|
| 4 |
datasets:
|
| 5 |
- prachuryyaIITG/CLASSER
|
| 6 |
language:
|
| 7 |
- ne
|
| 8 |
+
license: mit
|
| 9 |
metrics:
|
| 10 |
- f1
|
| 11 |
- precision
|
| 12 |
- recall
|
|
|
|
|
|
|
| 13 |
pipeline_tag: token-classification
|
| 14 |
+
library_name: transformers
|
| 15 |
tags:
|
| 16 |
- NER
|
| 17 |
- Named_Entity_Recognition
|
|
|
|
| 20 |
|
| 21 |
**MuRIL is fine-tuned on Nepali [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) dataset for Fine-grained Named Entity Recognition.**
|
| 22 |
|
| 23 |
+
This model is part of the work presented in the paper [AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers](https://huggingface.co/papers/2601.10161).
|
| 24 |
+
|
| 25 |
The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
|
| 26 |
|
| 27 |
* Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
|
|
|
|
| 113 |
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
|
| 114 |
pages={2027--2051},
|
| 115 |
year={2023}
|
| 116 |
+
}
|
| 117 |
+
```
|