Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ajtamayoh/Curso_NLP_UdeA_Sequence_Classification_Example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajtamayoh/Curso_NLP_UdeA_Sequence_Classification_Example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ajtamayoh/Curso_NLP_UdeA_Sequence_Classification_Example")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ajtamayoh/Curso_NLP_UdeA_Sequence_Classification_Example") model = AutoModelForSequenceClassification.from_pretrained("ajtamayoh/Curso_NLP_UdeA_Sequence_Classification_Example") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 2
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267832560
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:30d902567c5c5e956e6634fc2570e958c3abe7550ac7d579e0694d974ed31c98
|
| 3 |
size 267832560
|