Instructions to use Narsil/pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/pretrained with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Narsil/pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Narsil/pretrained: direct link, hf CLI and curl.
- Browser
- Download file 698 Bytes
-
https://huggingface.co/Narsil/pretrained/resolve/main/config.json
- Command line
-
hf download hf://Narsil/pretrained/config.json
-
curl -L -o config.json https://huggingface.co/Narsil/pretrained/resolve/main/config.json
698 Bytes
| { | |
| "attn_pdrop": 0.1, | |
| "embd_pdrop": 0.1, | |
| "finetuning_task": null, | |
| "id2label": { | |
| "0": "LABEL_0" | |
| }, | |
| "initializer_range": 0.02, | |
| "is_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0 | |
| }, | |
| "layer_norm_epsilon": 1e-05, | |
| "n_ctx": 1024, | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_layer": 6, | |
| "n_positions": 1024, | |
| "num_labels": 1, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "output_past": true, | |
| "pruned_heads": {}, | |
| "resid_pdrop": 0.1, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "torchscript": false, | |
| "use_bfloat16": false, | |
| "vocab_size": 50257 | |
| } | |