Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
unsloth
text-embeddings-inference
Instructions to use PiGrieco/OpenSesame with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PiGrieco/OpenSesame with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PiGrieco/OpenSesame")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PiGrieco/OpenSesame") model = AutoModelForSequenceClassification.from_pretrained("PiGrieco/OpenSesame") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use PiGrieco/OpenSesame with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PiGrieco/OpenSesame to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for PiGrieco/OpenSesame to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for PiGrieco/OpenSesame to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="PiGrieco/OpenSesame", max_seq_length=2048, )
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 16 |
|
| 17 |
# OpenSesame
|
| 18 |
|
| 19 |
-
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the
|
| 20 |
It achieves the following results on the evaluation set:
|
| 21 |
- Loss: 0.2134
|
| 22 |
- Accuracy: 0.9469
|
|
|
|
| 16 |
|
| 17 |
# OpenSesame
|
| 18 |
|
| 19 |
+
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [this](https://assets-eu.researchsquare.com/files/rs-2370113/v1/090f670e-87cd-40e8-8bf1-51fa9c02d105.pdf?c=1671622196) dataset.
|
| 20 |
It achieves the following results on the evaluation set:
|
| 21 |
- Loss: 0.2134
|
| 22 |
- Accuracy: 0.9469
|