Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Trained with AutoTrain
text-embeddings-inference
Instructions to use idobn/twitter-mbti-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idobn/twitter-mbti-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="idobn/twitter-mbti-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("idobn/twitter-mbti-v2") model = AutoModelForSequenceClassification.from_pretrained("idobn/twitter-mbti-v2") - Notebooks
- Google Colab
- Kaggle
File size: 1,486 Bytes
75449cb | 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 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | {
"_name_or_path": "microsoft/deberta-v3-large",
"_num_labels": 16,
"architectures": [
"DebertaV2ForSequenceClassification"
],
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"id2label": {
"0": "enfj",
"1": "enfp",
"2": "entj",
"3": "entp",
"4": "esfj",
"5": "esfp",
"6": "estj",
"7": "estp",
"8": "infj",
"9": "infp",
"10": "intj",
"11": "intp",
"12": "isfj",
"13": "isfp",
"14": "istj",
"15": "istp"
},
"initializer_range": 0.02,
"intermediate_size": 4096,
"label2id": {
"enfj": 0,
"enfp": 1,
"entj": 2,
"entp": 3,
"esfj": 4,
"esfp": 5,
"estj": 6,
"estp": 7,
"infj": 8,
"infp": 9,
"intj": 10,
"intp": 11,
"isfj": 12,
"isfp": 13,
"istj": 14,
"istp": 15
},
"layer_norm_eps": 1e-07,
"legacy": true,
"max_position_embeddings": 512,
"max_relative_positions": -1,
"model_type": "deberta-v2",
"norm_rel_ebd": "layer_norm",
"num_attention_heads": 16,
"num_hidden_layers": 24,
"pad_token_id": 0,
"pooler_dropout": 0,
"pooler_hidden_act": "gelu",
"pooler_hidden_size": 1024,
"pos_att_type": [
"p2c",
"c2p"
],
"position_biased_input": false,
"position_buckets": 256,
"relative_attention": true,
"share_att_key": true,
"torch_dtype": "float32",
"transformers_version": "4.48.0",
"type_vocab_size": 0,
"vocab_size": 128100
}
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