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 sha256:7f0277767ad795974455eeed18812f64ff35fda2fb802428eda011ba34780acd
|
| 3 |
size 267854321
|
runs/May23_21-36-51_f9b56511b52a/events.out.tfevents.1653341931.f9b56511b52a.74.0
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 sha256:71681127602fa6f7b475670949676a59f7386f679aa00da6e2e85d8d2bf39c76
|
| 3 |
+
size 3812
|
runs/May23_21-36-51_f9b56511b52a/events.out.tfevents.1653342029.f9b56511b52a.74.2
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2b38cbed07da07dcb71e06b6d2096abb6889364d4a5b899143966ec58818db92
|
| 3 |
+
size 409
|