Text Classification
Transformers
TensorBoard
Safetensors
opt
trl
reward-trainer
reward
Generated from Trainer
Instructions to use thobauma/opt-350m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thobauma/opt-350m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thobauma/opt-350m")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thobauma/opt-350m") model = AutoModelForSequenceClassification.from_pretrained("thobauma/opt-350m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_bos_token": true, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "1": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "bos_token": "</s>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "model_max_length": 2048, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "</s>" | |
| } | |