Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Mutugi/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mutugi/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mutugi/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mutugi/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("Mutugi/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Apr13_08-28-22_3f50d9a1dfe6/events.out.tfevents.1681374706.3f50d9a1dfe6.324.0
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 sha256:39b6f56037300cba90264fffe9379f2fecc6e3923bb0fd8304a02e0c4d36b676
|
| 3 |
+
size 4263
|
runs/Apr13_08-28-22_3f50d9a1dfe6/events.out.tfevents.1681375955.3f50d9a1dfe6.324.2
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:15dbe1f880da37f3628b8f0a8fcaa9ed3ae8639bab5f1a6a7e467bd658c2ee27
|
| 3 |
+
size 457
|