Instructions to use kdearsty/llama-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kdearsty/llama-testing with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("stas/tiny-random-llama-2") model = PeftModel.from_pretrained(base_model, "kdearsty/llama-testing") - Notebooks
- Google Colab
- Kaggle
File size: 384 Bytes
ce21a05 | 1 2 3 4 5 6 7 8 9 10 | {
"bos_token": "",
"eos_token": "",
"model_max_length": 1000000000000000019884624838656,
"name_or_path": "decapoda-research/llama-7b-hf",
"special_tokens_map_file": "/home/kat/.cache/huggingface/hub/models--decapoda-research--llama-7b-hf/snapshots/5f98eefcc80e437ef68d457ad7bf167c2c6a1348/special_tokens_map.json",
"tokenizer_class": "LLaMATokenizer",
"unk_token": ""
}
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