Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use universalner/uner_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_all") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_all") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (76b5796c316496e29ae71105e8f711db003a9f52)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:94f4c4725e65c7797433e33000eff13d9e85ff7ecf3899e4c6f755eb4de0b32c
|
| 3 |
+
size 2235448756
|