Token Classification
Transformers
PyTorch
xlm-roberta
linguistics
cognition
methaphors
information-extraction
classification
cognitive-linguistics
conceptual-metaphors
Instructions to use lwachowiak/Metaphor-Detection-XLMR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lwachowiak/Metaphor-Detection-XLMR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lwachowiak/Metaphor-Detection-XLMR")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lwachowiak/Metaphor-Detection-XLMR") model = AutoModelForTokenClassification.from_pretrained("lwachowiak/Metaphor-Detection-XLMR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
43fd6b3
1
Parent(s): b7fce5f
Upload training_args.bin with git-lfs
Browse files- training_args.bin +3 -0
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:75d45a0058bf26f1d59f8aaad091dcfc9869a132b1b866171da10162ccfc6452
|
| 3 |
+
size 2991
|