Instructions to use techopolis/Assistive-Technology-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use techopolis/Assistive-Technology-trainer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-1b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "techopolis/Assistive-Technology-trainer") - Notebooks
- Google Colab
- Kaggle
Download config.json from techopolis/Assistive-Technology-trainer: direct link, hf CLI and curl.
- Browser
- Download file 344 Bytes
-
https://huggingface.co/techopolis/Assistive-Technology-trainer/resolve/main/config.json
- Command line
-
hf download hf://techopolis/Assistive-Technology-trainer/config.json
-
curl -L -o config.json https://huggingface.co/techopolis/Assistive-Technology-trainer/resolve/main/config.json
344 Bytes
| { | |
| "model_name": "assistive_technology", | |
| "output_file": "C:\\Users\\miked\\Documents\\ai training\\assistive_technology.gguf", | |
| "precision": "f16", | |
| "conversion_tool": "convert_hf_to_gguf.py", | |
| "tokenizer": "llama-bpe", | |
| "framework": "transformers", | |
| "notes": "Model converted to GGUF format with precision f16." | |
| } |