Instructions to use Jarnails1559/sentiment-analyzer-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jarnails1559/sentiment-analyzer-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jarnails1559/sentiment-analyzer-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Jarnails1559/sentiment-analyzer-model: direct link, hf CLI and curl.
- Browser
- Download file 438 Bytes
-
https://huggingface.co/Jarnails1559/sentiment-analyzer-model/resolve/main/config.json
- Command line
-
hf download hf://Jarnails1559/sentiment-analyzer-model/config.json
-
curl -L -o config.json https://huggingface.co/Jarnails1559/sentiment-analyzer-model/resolve/main/config.json
438 Bytes
| { | |
| "attn_pdrop": 0.1, | |
| "embd_pdrop": 0.1, | |
| "layer_norm_epsilon": 1e-5, | |
| "model_type": "gpt2", | |
| "n_head": 12, | |
| "n_layer": 12, | |
| "n_embd": 768, | |
| "resid_pdrop": 0.1, | |
| "initializer_range": 0.02, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "summary_activation": null, | |
| "summary_proj_to_labels": true, | |
| "summary_first_dropout": 0.1, | |
| "summary_last_dropout": 0.1, | |
| "vocab_size": 50257, | |
| "framework": "tensorflow" | |
| } | |