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
Download generation_config.json from RahulPi/Email_Text_Formatter: direct link, hf CLI and curl.
- Browser
- Download file 180 Bytes
-
https://huggingface.co/RahulPi/Email_Text_Formatter/resolve/main/generation_config.json
- Command line
-
hf download hf://RahulPi/Email_Text_Formatter/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/RahulPi/Email_Text_Formatter/resolve/main/generation_config.json
180 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 100257, | |
| "eos_token_id": [ | |
| 100265 | |
| ], | |
| "max_length": 16384, | |
| "pad_token_id": 100351, | |
| "transformers_version": "4.57.1" | |
| } | |