Instructions to use Mathoctopus/Parallel_33B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathoctopus/Parallel_33B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Mathoctopus/Parallel_33B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Mathoctopus/Parallel_33B") model = AutoModel.from_pretrained("Mathoctopus/Parallel_33B") - Notebooks
- Google Colab
- Kaggle
Commit ·
68bdf1d
1
Parent(s): 54e65b1
Update README.md
Browse files
README.md
CHANGED
|
@@ -41,6 +41,8 @@ Our dataset and models are all available at Huggingface.
|
|
| 41 |
|
| 42 |
🤗 [MGSM8KInstruct_Parallel Dataset](https://huggingface.co/datasets/Mathoctopus/GSM8KInstruct_Parallel)
|
| 43 |
|
|
|
|
|
|
|
| 44 |
🤗 [MSVAMP Dataset](https://huggingface.co/datasets/Mathoctopus/MSVAMP)
|
| 45 |
|
| 46 |
|
|
|
|
| 41 |
|
| 42 |
🤗 [MGSM8KInstruct_Parallel Dataset](https://huggingface.co/datasets/Mathoctopus/GSM8KInstruct_Parallel)
|
| 43 |
|
| 44 |
+
🤗 [MGSM8KInstruct_Cross Dataset](https://huggingface.co/datasets/Mathoctopus/MGSM8KInstruct_Cross)
|
| 45 |
+
|
| 46 |
🤗 [MSVAMP Dataset](https://huggingface.co/datasets/Mathoctopus/MSVAMP)
|
| 47 |
|
| 48 |
|