Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use petermutwiri/NLP_Capstone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petermutwiri/NLP_Capstone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="petermutwiri/NLP_Capstone")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("petermutwiri/NLP_Capstone") model = AutoModelForSequenceClassification.from_pretrained("petermutwiri/NLP_Capstone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
b1b910b
1
Parent(s): fc4ec5d
Training in progress, step 2500
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498658094
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8e0c7d508ba22f7bd2038f7cb5d7cea92abbc7900b2688d27828520ce536bf18
|
| 3 |
size 498658094
|