Instructions to use tulayaka/loadtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tulayaka/loadtest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tulayaka/loadtest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tulayaka/loadtest") model = AutoModelForSequenceClassification.from_pretrained("tulayaka/loadtest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete config.json
Browse files- config.json +0 -4
config.json
DELETED
|
@@ -1,4 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"torch_dtype": "float16",
|
| 3 |
-
"model_type": "llama"
|
| 4 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|