Token Classification
Transformers
Safetensors
Thai
camembert
ner
thai
phayathaibert
job-posting
apple-silicon
Eval Results (legacy)
Instructions to use chayuto/thai-job-ner-phayathaibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chayuto/thai-job-ner-phayathaibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chayuto/thai-job-ner-phayathaibert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chayuto/thai-job-ner-phayathaibert") model = AutoModelForTokenClassification.from_pretrained("chayuto/thai-job-ner-phayathaibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,450 Bytes
1700972 | 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 | {
"add_cross_attention": false,
"architectures": [
"CamembertForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 0,
"classifier_dropout": null,
"dtype": "float32",
"eos_token_id": 2,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "O",
"1": "B-HARD_SKILL",
"2": "I-HARD_SKILL",
"3": "B-PERSON",
"4": "I-PERSON",
"5": "B-LOCATION",
"6": "I-LOCATION",
"7": "B-COMPENSATION",
"8": "I-COMPENSATION",
"9": "B-EMPLOYMENT_TERMS",
"10": "I-EMPLOYMENT_TERMS",
"11": "B-CONTACT",
"12": "I-CONTACT",
"13": "B-DEMOGRAPHIC",
"14": "I-DEMOGRAPHIC"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": false,
"label2id": {
"B-COMPENSATION": 7,
"B-CONTACT": 11,
"B-DEMOGRAPHIC": 13,
"B-EMPLOYMENT_TERMS": 9,
"B-HARD_SKILL": 1,
"B-LOCATION": 5,
"B-PERSON": 3,
"I-COMPENSATION": 8,
"I-CONTACT": 12,
"I-DEMOGRAPHIC": 14,
"I-EMPLOYMENT_TERMS": 10,
"I-HARD_SKILL": 2,
"I-LOCATION": 6,
"I-PERSON": 4,
"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",
"transformers_version": "5.3.0",
"type_vocab_size": 1,
"use_cache": false,
"vocab_size": 249262
}
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