holylovenia commited on
Commit
9f3965f
1 Parent(s): 421a09a

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +16 -16
README.md CHANGED
@@ -12,13 +12,13 @@ tags:
12
 
13
  This dataset is designed for named entity recognition (NER) tasks in the Bahasa Indonesia tourism domain. It contains labeled sequences of named entities, including locations, facilities, and tourism-related entities. The dataset is annotated with the following entity types:
14
 
15
- O (0) : Non-entity or other words not falling into the specified categories.
16
- B-WIS (1): Beginning of a tourism-related entity.
17
- I-WIS (2): Continuation of a tourism-related entity.
18
- B-LOC (3): Beginning of a location entity.
19
- I-LOC (4): Continuation of a location entity.
20
- B-FAS (5): Beginning of a facility entity.
21
- I-FAS (6): Continuation of a facility entity.
22
 
23
 
24
  ## Languages
@@ -28,25 +28,25 @@ ind
28
  ## Supported Tasks
29
 
30
  Named Entity Recognition
31
-
32
  ## Dataset Usage
33
  ### Using `datasets` library
34
  ```
35
- from datasets import load_dataset
36
- dset = datasets.load_dataset("SEACrowd/indoner_tourism", trust_remote_code=True)
37
  ```
38
  ### Using `seacrowd` library
39
  ```import seacrowd as sc
40
  # Load the dataset using the default config
41
- dset = sc.load_dataset("indoner_tourism", schema="seacrowd")
42
  # Check all available subsets (config names) of the dataset
43
- print(sc.available_config_names("indoner_tourism"))
44
  # Load the dataset using a specific config
45
- dset = sc.load_dataset_by_config_name(config_name="<config_name>")
46
  ```
47
-
48
- More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
49
-
50
 
51
  ## Dataset Homepage
52
 
 
12
 
13
  This dataset is designed for named entity recognition (NER) tasks in the Bahasa Indonesia tourism domain. It contains labeled sequences of named entities, including locations, facilities, and tourism-related entities. The dataset is annotated with the following entity types:
14
 
15
+ O (0): Non-entity or other words not falling into the specified categories.
16
+ B-WIS (1): Beginning of a tourism-related entity.
17
+ I-WIS (2): Continuation of a tourism-related entity.
18
+ B-LOC (3): Beginning of a location entity.
19
+ I-LOC (4): Continuation of a location entity.
20
+ B-FAS (5): Beginning of a facility entity.
21
+ I-FAS (6): Continuation of a facility entity.
22
 
23
 
24
  ## Languages
 
28
  ## Supported Tasks
29
 
30
  Named Entity Recognition
31
+
32
  ## Dataset Usage
33
  ### Using `datasets` library
34
  ```
35
+ from datasets import load_dataset
36
+ dset = datasets.load_dataset("SEACrowd/indoner_tourism", trust_remote_code=True)
37
  ```
38
  ### Using `seacrowd` library
39
  ```import seacrowd as sc
40
  # Load the dataset using the default config
41
+ dset = sc.load_dataset("indoner_tourism", schema="seacrowd")
42
  # Check all available subsets (config names) of the dataset
43
+ print(sc.available_config_names("indoner_tourism"))
44
  # Load the dataset using a specific config
45
+ dset = sc.load_dataset_by_config_name(config_name="<config_name>")
46
  ```
47
+
48
+ More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
49
+
50
 
51
  ## Dataset Homepage
52