Text Generation
PEFT
Safetensors
quantum-computing
bitnet
lora
algorithm-recommendation
research-prototype
Instructions to use UlukaDev/qare-bitnet-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use UlukaDev/qare-bitnet-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/bitnet-b1.58-2B-4T-bf16") model = PeftModel.from_pretrained(base_model, "UlukaDev/qare-bitnet-lora") - Notebooks
- Google Colab
- Kaggle
File size: 379 Bytes
8a46533 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"backend": "tokenizers",
"bos_token": "<|begin_of_text|>",
"clean_up_tokenization_spaces": true,
"eos_token": "<|eot_id|>",
"is_local": false,
"local_files_only": false,
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<|eot_id|>",
"tokenizer_class": "TokenizersBackend"
}
|