Text Generation
PEFT
Safetensors
English
Hindi
function-calling
tool-use
customer-support
lora
functiongemma
conversational
Instructions to use CuriousDragon/northline-functiongemma-270m-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CuriousDragon/northline-functiongemma-270m-sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/functiongemma-270m-it") model = PeftModel.from_pretrained(base_model, "CuriousDragon/northline-functiongemma-270m-sft") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CuriousDragon/northline-functiongemma-270m-sft: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/CuriousDragon/northline-functiongemma-270m-sft/resolve/main/tokenizer.json
- Command line
-
hf download hf://CuriousDragon/northline-functiongemma-270m-sft/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CuriousDragon/northline-functiongemma-270m-sft/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 74f7059f05cfcc5dc6a2016f18c62e60e864f3dfefd2b33bdc4a8d55effed320
- Size of remote file:
- 33.4 MB
- SHA256:
- 80d7f800b949accd7eb940bac75e642f9468e4df157403032a55bf54ed23b650
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