Instructions to use tomerRest/line_item_categories with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomerRest/line_item_categories with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomerRest/line_item_categories")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tomerRest/line_item_categories") model = AutoModelForSequenceClassification.from_pretrained("tomerRest/line_item_categories", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +37 -45
- model.safetensors +2 -2
config.json
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"hidden_dim": 3072,
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"id2label": {
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"0": "Beverages_Alcoholic Beverages_Beers and Ciders",
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"1": "Beverages_Alcoholic
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"2": "Beverages_Alcoholic
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"3": "
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"4": "Beverages_Non-Alcoholic
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"5": "Beverages_Non-Alcoholic
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"6": "Beverages_Non-Alcoholic
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"7": "Beverages_Non-Alcoholic
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"8": "
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"9": "Cleaning and Packaging Products_Cleaning
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"10": "Cleaning and Packaging Products_Cleaning
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"11": "Cleaning and Packaging
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"12": "Cleaning and Packaging
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"13": "Cleaning and Packaging
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"14": "
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"15": "
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"16": "
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"17": "
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"18": "
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"19": "
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"20": "
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"21": "Food_Dry and Canned
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"22": "Food_Dry and Canned
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"23": "Food_Dry and Canned
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"24": "
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"25": "
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"26": "Food_Fresh
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"27": "Food_Fresh
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"28": "
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"29": "
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"30": "
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"31": "
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"32": "
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"33": "
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"34": "
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"35": "
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"36": "
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"37": "
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"38": "Food_Prepared Food_Other",
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"39": "Food_Sweets and Candies_Confectioneries",
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"40": "Food_Sweets and Candies_Other",
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"41": "Other_Non-Food Items_Other"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_35": 35,
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"LABEL_36": 36,
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"LABEL_37": 37,
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"LABEL_38": 38,
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"LABEL_39": 39,
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"LABEL_4": 4,
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"LABEL_40": 40,
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"LABEL_41": 41,
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"LABEL_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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"hidden_dim": 3072,
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"id2label": {
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"0": "Beverages_Alcoholic Beverages_Beers and Ciders",
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"1": "Beverages_Alcoholic Beverages_Spirits",
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"2": "Beverages_Alcoholic Beverages_Wines",
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"3": "Beverages_Non-Alcoholic Beverages_Hot Beverages",
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"4": "Beverages_Non-Alcoholic Beverages_Juices",
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"5": "Beverages_Non-Alcoholic Beverages_Other",
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"6": "Beverages_Non-Alcoholic Beverages_Soft Drinks",
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"7": "Beverages_Non-Alcoholic Beverages_Water",
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"8": "Cleaning and Packaging Products_Cleaning Supplies_Cleaning Liquids",
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"9": "Cleaning and Packaging Products_Cleaning Supplies_Gloves",
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"10": "Cleaning and Packaging Products_Cleaning Supplies_Other",
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"11": "Cleaning and Packaging Products_Other_Other",
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"12": "Cleaning and Packaging Products_Packaging_Lids",
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"13": "Cleaning and Packaging Products_Packaging_Other",
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"14": "Food_Dairy_Cheese",
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"15": "Food_Dairy_Cream",
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"16": "Food_Dairy_Non-dairy substitutes",
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"17": "Food_Dairy_Other",
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"18": "Food_Dairy_milk",
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"19": "Food_Dry and Canned Goods_Baked Goods and Snacks",
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"20": "Food_Dry and Canned Goods_Baking Supplies",
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"21": "Food_Dry and Canned Goods_Condiments, Sauces, and Spreads",
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"22": "Food_Dry and Canned Goods_Other",
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"23": "Food_Dry and Canned Goods_Nuts, Seeds, and Grains",
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"24": "Food_Fresh Produce_Eggs",
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"25": "Food_Fresh Produce_Fruit",
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"26": "Food_Fresh Produce_Other",
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"27": "Food_Fresh Produce_Vegetables",
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"28": "Food_Herbs and Spices_Herbs",
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"29": "Food_Herbs and Spices_Spices",
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"30": "Food_Meat and Seafood_Meat and Meat Products",
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"31": "Food_Meat and Seafood_Seafood",
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"32": "Food_Oils and Vinegars_Oils",
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"33": "Food_Prepared Food_Appetizers",
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"34": "Food_Prepared Food_Other",
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"35": "Food_Sweets and Candies_Confectioneries",
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"36": "Food_Sweets and Candies_Other",
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"37": "Other_Non-Food Items_Other"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_35": 35,
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"LABEL_37": 37,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 267943312
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