Instructions to use gesh75/netops-intent2cli-qwen0.5b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gesh75/netops-intent2cli-qwen0.5b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "gesh75/netops-intent2cli-qwen0.5b-lora") - Notebooks
- Google Colab
- Kaggle
Download qa_data.json from gesh75/netops-intent2cli-qwen0.5b-lora: direct link, hf CLI and curl.
- Browser
- Download file 406 Bytes
-
https://huggingface.co/gesh75/netops-intent2cli-qwen0.5b-lora/resolve/main/qa_data.json
- Command line
-
hf download hf://gesh75/netops-intent2cli-qwen0.5b-lora/qa_data.json
-
curl -L -o qa_data.json https://huggingface.co/gesh75/netops-intent2cli-qwen0.5b-lora/resolve/main/qa_data.json
406 Bytes
| { | |
| "passed": true, | |
| "published_corpus_rows": 70006, | |
| "new_pairs": 738, | |
| "new_pairs_exact_command_membership": 738, | |
| "new_pairs_vendor_os_membership": 738, | |
| "work_estate_term_hits": 0, | |
| "command_split_overlap": 0, | |
| "original_val_test_objects_unchanged": true, | |
| "firewall_action_polarity_checked": true, | |
| "source_parquet_sha256": "19483dbca62b997de65b099fc6b72f1f9caa0d2f9d85092fed9c68e60df212f4" | |
| } |