Instructions to use funnel-transformer/xlarge-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/xlarge-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/xlarge-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/xlarge-base") model = AutoModel.from_pretrained("funnel-transformer/xlarge-base") - Notebooks
- Google Colab
- Kaggle
Updates incorrect tokenizer configuration file
#2
by lysandre HF Staff - opened
- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>", "bos_token": "<s>", "eos_token": "</s>"}
|
|
|
|
| 1 |
+
{"unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>", "bos_token": "<s>", "eos_token": "</s>", "do_lower_case": true, "model_max_length": 512}
|