Instructions to use CleveGreen/FieldClassifier_v2_gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CleveGreen/FieldClassifier_v2_gpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CleveGreen/FieldClassifier_v2_gpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CleveGreen/FieldClassifier_v2_gpt") model = AutoModelForSequenceClassification.from_pretrained("CleveGreen/FieldClassifier_v2_gpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from CleveGreen/FieldClassifier_v2_gpt: direct link, hf CLI and curl.
- Browser
- Download file 307 Bytes
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https://huggingface.co/CleveGreen/FieldClassifier_v2_gpt/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://CleveGreen/FieldClassifier_v2_gpt/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/CleveGreen/FieldClassifier_v2_gpt/resolve/main/tokenizer_config.json
307 Bytes
| {"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "C:\\Users\\clell\\PycharmProjects\\resume_parser\\models\\field-classifier2", "tokenizer_class": "GPT2Tokenizer"} |