Instructions to use trl-internal-testing/tiny-LlamaForSequenceClassification-3.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-LlamaForSequenceClassification-3.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trl-internal-testing/tiny-LlamaForSequenceClassification-3.2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-LlamaForSequenceClassification-3.2") model = AutoModelForSequenceClassification.from_pretrained("trl-internal-testing/tiny-LlamaForSequenceClassification-3.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": { | |
| "content": "<|begin_of_text|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "content": "<|eot_id|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |