Text Generation
PEFT
Safetensors
English
llama4_text
adaption-labs
autoscientist
legal
contract-clause-classification
cuad
hearsay
statutory-entailment
lora
hackathon
conversational
4-bit precision
bitsandbytes
Instructions to use narendarcodes/adaption-contract-clause-analyzer-109b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use narendarcodes/adaption-contract-clause-analyzer-109b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit") model = PeftModel.from_pretrained(base_model, "narendarcodes/adaption-contract-clause-analyzer-109b") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|begin_of_text|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|eot|>", | |
| "is_local": false, | |
| "local_files_only": true, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 10485760, | |
| "pad_token": "<|finetune_right_pad|>", | |
| "padding_side": "right", | |
| "processor_class": "Llama4Processor", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |