Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use BaxterAI/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaxterAI/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaxterAI/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaxterAI/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("BaxterAI/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267854321
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4e9574cbbdfc7c63f4383c5658c51a30a09f75222ceed3fd7856814b82c5ce96
|
| 3 |
size 267854321
|
runs/May24_00-31-54_ece63acfea1f/events.out.tfevents.1653352412.ece63acfea1f.73.0
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 sha256:6434789fb6666b441a59a282db8839af747cd91d2bac8d3518db7dade44dac9c
|
| 3 |
+
size 8523
|
runs/May24_00-31-54_ece63acfea1f/events.out.tfevents.1653355064.ece63acfea1f.73.2
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:465bd77e881e527396f65b26e48245b762b2f4dbfc83de457b715d39db614582
|
| 3 |
+
size 409
|