Instructions to use somaia02/noon-gec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use somaia02/noon-gec with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Naseej/noon-7b") model = PeftModel.from_pretrained(base_model, "somaia02/noon-gec") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "Naseej/noon-7b", | |
| "inference_mode": true, | |
| "num_attention_heads": 32, | |
| "num_layers": 30, | |
| "num_transformer_submodules": 1, | |
| "num_virtual_tokens": 100, | |
| "peft_type": "PROMPT_TUNING", | |
| "prompt_tuning_init": "TEXT", | |
| "prompt_tuning_init_text": "\u0623\u0646\u062a \u0627\u0644\u0622\u0646 \u062e\u0628\u064a\u0631 \u0641\u064a \u0639\u0644\u0648\u0645 \u0627\u0644\u0644\u063a\u0629 \u0627\u0644\u0639\u0631\u0628\u064a\u0629 \u0648\u0643\u064a\u0641\u064a\u0629 \u062a\u0635\u062d\u064a\u062d \u0627\u0644\u0623\u062e\u0637\u0627\u0621 \u0627\u0644\u0644\u063a\u0648\u064a\u0629 \u0648\u0627\u0644\u0625\u0645\u0644\u0627\u0626\u064a\u0629. \u0647\u062f\u0641\u0643 \u0647\u0648 \u0625\u0639\u0627\u062f\u0629 \u0643\u062a\u0627\u0628\u0629 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u0645\u062f\u062e\u0644\u0629 \u0628\u0639\u062f \u062a\u0635\u062d\u064a\u062d \u0627\u0644\u0623\u062e\u0637\u0627\u0621 \u0627\u0644\u0644\u063a\u0648\u064a\u0629 \u0648\u0627\u0644\u0625\u0645\u0644\u0627\u0626\u064a\u0629. \u0644\u0627 \u062a\u0642\u0645 \u0628\u0625\u0639\u0627\u062f\u0629 \u0635\u064a\u0627\u063a\u0629 \u0627\u0644\u062c\u0645\u0644\u0629. \u0644\u0627 \u062a\u0642\u0645 \u0628\u0625\u0636\u0627\u0641\u0629 \u062c\u0645\u0644 \u062c\u062f\u064a\u062f\u0629 \u063a\u064a\u0631 \u0645\u062a\u0648\u0627\u062c\u062f\u0629 \u0628\u0627\u0644\u0646\u0635 \u0627\u0644\u0623\u0635\u0644\u064a.", | |
| "revision": null, | |
| "task_type": "CAUSAL_LM", | |
| "token_dim": 4096, | |
| "tokenizer_name_or_path": "Naseej/noon-7b" | |
| } |