Instructions to use date3k2/mamba-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use date3k2/mamba-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="date3k2/mamba-text-classification", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("date3k2/mamba-text-classification", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("date3k2/mamba-text-classification", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files
README.md
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
---
|
| 2 |
-
base_model: state-spaces/mamba-130m-hf
|
| 3 |
tags:
|
| 4 |
- generated_from_trainer
|
|
|
|
| 5 |
metrics:
|
| 6 |
- accuracy
|
| 7 |
- f1
|
|
|
|
| 1 |
---
|
|
|
|
| 2 |
tags:
|
| 3 |
- generated_from_trainer
|
| 4 |
+
base_model: state-spaces/mamba-130m-hf
|
| 5 |
metrics:
|
| 6 |
- accuracy
|
| 7 |
- f1
|