Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
resume-parsing
nlp
text-embeddings-inference
Instructions to use amosify/resume-section-classifier-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amosify/resume-section-classifier-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amosify/resume-section-classifier-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amosify/resume-section-classifier-v1") model = AutoModelForSequenceClassification.from_pretrained("amosify/resume-section-classifier-v1") - Notebooks
- Google Colab
- Kaggle
File size: 1,349 Bytes
748fdb7 | 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 | {
"activation": "gelu",
"architectures": [
"DistilBertForSequenceClassification"
],
"attention_dropout": 0.1,
"bos_token_id": null,
"dim": 768,
"dropout": 0.1,
"dtype": "float32",
"eos_token_id": null,
"hidden_dim": 3072,
"id2label": {
"0": "projects",
"1": "certifications",
"2": "publications",
"3": "references",
"4": "education",
"5": "objective",
"6": "additional_info",
"7": "languages",
"8": "hobbies",
"9": "summary",
"10": "awards",
"11": "experience",
"12": "skills",
"13": "volunteer",
"14": "contact"
},
"initializer_range": 0.02,
"label2id": {
"additional_info": 6,
"awards": 10,
"certifications": 1,
"contact": 14,
"education": 4,
"experience": 11,
"hobbies": 8,
"languages": 7,
"objective": 5,
"projects": 0,
"publications": 2,
"references": 3,
"skills": 12,
"summary": 9,
"volunteer": 13
},
"max_position_embeddings": 512,
"model_type": "distilbert",
"n_heads": 12,
"n_layers": 6,
"pad_token_id": 0,
"problem_type": "single_label_classification",
"qa_dropout": 0.1,
"seq_classif_dropout": 0.2,
"sinusoidal_pos_embds": false,
"tie_weights_": true,
"tie_word_embeddings": true,
"transformers_version": "5.6.2",
"use_cache": false,
"vocab_size": 30522
}
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