Fill-Mask
Transformers
PyTorch
xlm-roberta
afrolm
active learning
language modeling
research papers
natural language processing
self-active learning
Instructions to use bonadossou/afrolm_active_learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bonadossou/afrolm_active_learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bonadossou/afrolm_active_learning")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bonadossou/afrolm_active_learning") model = AutoModelForMaskedLM.from_pretrained("bonadossou/afrolm_active_learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
74f6269
1
Parent(s): cae6c4b
Update tokenizer_config.json
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "tokenizer_250k"}
|
|
|
|
| 1 |
+
{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "tokenizer_250k"}
|