Instructions to use CLMBR/binding-case-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/binding-case-lstm-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/binding-case-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-915840/config.json from CLMBR/binding-case-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 549 Bytes
-
https://huggingface.co/CLMBR/binding-case-lstm-2/resolve/82fc90c4a650a6cbb094e0980f06f858c4219b9b/checkpoint-915840/config.json
- Command line
-
hf download hf://CLMBR/binding-case-lstm-2@82fc90c4a650a6cbb094e0980f06f858c4219b9b/checkpoint-915840/config.json
-
curl -L -o config.json https://huggingface.co/CLMBR/binding-case-lstm-2/resolve/82fc90c4a650a6cbb094e0980f06f858c4219b9b/checkpoint-915840/config.json
549 Bytes
| { | |
| "architectures": [ | |
| "RNNForLanguageModeling" | |
| ], | |
| "bidirectional": false, | |
| "dropout_p": 0.1, | |
| "emb_init_range": 0.1, | |
| "embedding_dim": 1024, | |
| "embedding_kwargs": {}, | |
| "hidden_dim": 1024, | |
| "lin_init_range": 0.03125, | |
| "lm_in_features": 1024, | |
| "model_type": "rnn", | |
| "num_layers": 2, | |
| "output_last_state": false, | |
| "output_recurrent_outputs": false, | |
| "recur_init_range": 0.03125, | |
| "rnn_kwargs": {}, | |
| "rnn_type": "LSTM", | |
| "tie_weights": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.33.3", | |
| "vocab_size": 50002 | |
| } | |