Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Centipede5/mbti_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Centipede5/mbti_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Centipede5/mbti_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Centipede5/mbti_model") model = AutoModelForSequenceClassification.from_pretrained("Centipede5/mbti_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
bffeefb
1
Parent(s): fee5f08
Training in progress, epoch 3
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267898605
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a14b7b45790d21a996b4730c200338a706b6485584cc7bf0444331ae1806fe93
|
| 3 |
size 267898605
|
runs/Jul19_04-52-02_13e0a65293ea/events.out.tfevents.1689742327.13e0a65293ea.28.5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d9bbddb1a12d1300bffc8e105aba8508df89aa78849fc739908f89271ee8c3a0
|
| 3 |
+
size 5671
|