Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use HugMaik/financial-twitter-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HugMaik/financial-twitter-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HugMaik/financial-twitter-sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HugMaik/financial-twitter-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("HugMaik/financial-twitter-sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Mar12_13-14-58_BendixSurface/events.out.tfevents.1678623314.BendixSurface.2924.0
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 sha256:86942ed59a7185f2caea49efdc7b71a6151fca7b950e17066c487ba58f1a5582
|
| 3 |
+
size 4564
|
runs/Mar12_13-14-58_BendixSurface/events.out.tfevents.1678625255.BendixSurface.2924.2
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1d6f8ac422744c11fb7d414c84bc0da9ae70fc4a2ca4bf94b8409a639bf2d63d
|
| 3 |
+
size 409
|