Instructions to use selimyagci/pm_task_llama_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use selimyagci/pm_task_llama_quantized with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("meta-llama/Llama-3.2-1B") model.load_adapter("selimyagci/pm_task_llama_quantized", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download head_config.json from selimyagci/pm_task_llama_quantized: direct link, hf CLI and curl.
- Browser
- Download file 270 Bytes
-
https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/head_config.json
- Command line
-
hf download hf://selimyagci/pm_task_llama_quantized/head_config.json
-
curl -L -o head_config.json https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/head_config.json
270 Bytes
| { | |
| "config": null, | |
| "hidden_size": 2048, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "model_class": "LlamaForCausalLM", | |
| "model_name": "meta-llama/Llama-3.2-1B", | |
| "model_type": "llama", | |
| "name": null, | |
| "num_labels": 2, | |
| "version": "adapters.1.0.0" | |
| } |