--- library_name: peft base_model: sujitvasanth/TheBloke-openchat-3.5-0106-GPTQ --- # Model Card for Model ID ## Model Details ### Model Description - **Developed by:** Dr Sujit Vasanth - **Model type:** QLoRA PEFT - **Language(s) (NLP):** Json, English - **License:** [More Information Needed] - **Finetuned from model [optional]:** TheBloke/openchat-3.5-0106-GPTQ ### Model Sources [optional] - **Repository:** https://github.com/sujitvasanth/GPTQ-finetune - **Demo [optional]:** https://github.com/sujitvasanth/GPTQ-finetune/blob/main/GPTQ-finetune.py ## How to Get Started with the Model model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config= GPTQConfig(bits=4, disable_exllama=False),device_map="auto") # is_trainable=True tokenizer = AutoTokenizer.from_pretrained(model_id) tokenizer.pad_token = tokenizer.eos_token model.load_adapter(adapter_id) ## Training Details ### Training Data https://huggingface.co/datasets/sujitvasanth/jsonsearch2 User: Assistant examples of Json search Query ### Training Procedure QLora PEFT training on custom dataset #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.8.2