Instructions to use FartLabs/FART_5M_H200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FartLabs/FART_5M_H200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FartLabs/FART_5M_H200")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FartLabs/FART_5M_H200") model = AutoModelForSequenceClassification.from_pretrained("FartLabs/FART_5M_H200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer
Verified signature1f11b64 -
Upload BertForSequenceClassification
Verified signature3950641 -
initial commit
Verified signature33c7f4d