Text Classification
Transformers
PyTorch
roberta
sequence-classification
biomedical
clinical
nlp
spanish
spanish-clinical
text-embeddings-inference
Instructions to use ELiRF/Chest-COVID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ELiRF/Chest-COVID with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ELiRF/Chest-COVID")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ELiRF/Chest-COVID") model = AutoModelForSequenceClassification.from_pretrained("ELiRF/Chest-COVID", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f3f85f74397e62353c6353ad1f13c0a1be862aa75dd7e40885cb0d7cd3f6e9e6
|
| 3 |
+
size 504540620
|