Instructions to use djamina/relatives_psr_seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djamina/relatives_psr_seq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="djamina/relatives_psr_seq")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("djamina/relatives_psr_seq") model = AutoModelForTokenClassification.from_pretrained("djamina/relatives_psr_seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from djamina/relatives_psr_seq: direct link, hf CLI and curl.
- Browser
- Download file 943 Bytes
-
https://huggingface.co/djamina/relatives_psr_seq/resolve/main/config.json
- Command line
-
hf download hf://djamina/relatives_psr_seq/config.json
-
curl -L -o config.json https://huggingface.co/djamina/relatives_psr_seq/resolve/main/config.json
943 Bytes
| { | |
| "architectures": [ | |
| "CamembertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-DET", | |
| "2": "I-DET", | |
| "3": "B-APPO", | |
| "4": "I-APPO", | |
| "5": "B-AMBIGUE", | |
| "6": "I-AMBIGUE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "B-AMBIGUE": 5, | |
| "B-APPO": 3, | |
| "B-DET": 1, | |
| "I-AMBIGUE": 6, | |
| "I-APPO": 4, | |
| "I-DET": 2, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "camembert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.41.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 500000 | |
| } | |