Instructions to use havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f/resolve/main/training_args.bin
- Command line
-
hf download hf://havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/havinash-ai/8716aa41-261a-4017-8f25-515daad74e0f/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- dad1be7de4ffd04ac183d140e3fbae9dfa57b91290847875352584dd7c946be6
- Size of remote file:
- 6.78 kB
- SHA256:
- 0600b0bb70c59ad2768220eef793989658ce184765e709dc646662cb41480ebb
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