Feature Extraction
Transformers
Safetensors
English
llama
text-generation
text-generation-inference
unsloth
phi-4
information-extraction
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use RahulPi/Email_Text_Formatter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RahulPi/Email_Text_Formatter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="RahulPi/Email_Text_Formatter")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RahulPi/Email_Text_Formatter") model = AutoModelForCausalLM.from_pretrained("RahulPi/Email_Text_Formatter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop