Text Generation
PEFT
Safetensors
English
text-to-sql
postgis
spatial-sql
city-information-modeling
cim
fine-tuned
qlora
conversational
Instructions to use taherdoust/llama31-8b-cim-q2sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use taherdoust/llama31-8b-cim-q2sql with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "taherdoust/llama31-8b-cim-q2sql") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from taherdoust/llama31-8b-cim-q2sql: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/taherdoust/llama31-8b-cim-q2sql/resolve/main/tokenizer.json
- Command line
-
hf download hf://taherdoust/llama31-8b-cim-q2sql/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/taherdoust/llama31-8b-cim-q2sql/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.