Instructions to use Ahatsham/Llama_MFAFY_Feature_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ahatsham/Llama_MFAFY_Feature_2 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "Ahatsham/Llama_MFAFY_Feature_2") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Ahatsham/Llama_MFAFY_Feature_2: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/Ahatsham/Llama_MFAFY_Feature_2/resolve/main/tokenizer.json
- Command line
-
hf download hf://Ahatsham/Llama_MFAFY_Feature_2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Ahatsham/Llama_MFAFY_Feature_2/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- e3047f8e350d56331912eda0f4dcb4d2279f3b8cec7fd05cab9194c308a8e1fa
- Size of remote file:
- 17.2 MB
- SHA256:
- 00224c78475a2ff2e27556796824b19aed9bd853b1925d36728fd05fd9d7693b
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