Text Classification
Transformers
TensorBoard
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use Katkatkuu/ESG_Prediction_IS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Katkatkuu/ESG_Prediction_IS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Katkatkuu/ESG_Prediction_IS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Katkatkuu/ESG_Prediction_IS") model = AutoModelForSequenceClassification.from_pretrained("Katkatkuu/ESG_Prediction_IS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,015 Bytes
3eb8e3c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | {
"_name_or_path": "airesearch/wangchanberta-base-att-spm-uncased",
"architectures": [
"CamembertForSequenceClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "Social&People",
"1": "Governance",
"2": "Environment"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"Environment": 2,
"Governance": 1,
"Social&People": 0
},
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "camembert",
"num_attention_head": 12,
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"problem_type": "single_label_classification",
"torch_dtype": "float32",
"transformers_version": "4.37.2",
"type_vocab_size": 1,
"use_cache": true,
"vocab_size": 25005
}
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