Instructions to use CleveGreen/JobClassifier_v2_gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CleveGreen/JobClassifier_v2_gpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CleveGreen/JobClassifier_v2_gpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CleveGreen/JobClassifier_v2_gpt") model = AutoModelForSequenceClassification.from_pretrained("CleveGreen/JobClassifier_v2_gpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 305 Bytes
ce8f12e | 1 | {"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\\job-classifier2", "tokenizer_class": "GPT2Tokenizer"} |