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 checkpoint-4146/training_args.bin from taherdoust/llama31-8b-cim-q2sql: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/taherdoust/llama31-8b-cim-q2sql/resolve/main/checkpoint-4146/training_args.bin
- Command line
-
hf download hf://taherdoust/llama31-8b-cim-q2sql/checkpoint-4146/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/taherdoust/llama31-8b-cim-q2sql/resolve/main/checkpoint-4146/training_args.bin
5.3 kB
- Xet hash:
- 593c0c88734953e87a6c025cc86e31c48a3ac9d7af3ad1dcca6412500148b28e
- Size of remote file:
- 5.3 kB
- SHA256:
- 70cea56a0e2ba72e52a576a9ac47a279083e3f164c653bbc79b2e20dce4ac045
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