Instructions to use CaseLoop/rights-navigator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CaseLoop/rights-navigator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CaseLoop/rights-navigator") model = AutoModelForSeq2SeqLM.from_pretrained("CaseLoop/rights-navigator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 765 Bytes
50a8ea3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import os
from huggingface_hub import HfApi
from transformers import AutoConfig, AutoModelForSeq2SeqLM
LOCAL_DIR = "./models/saved_simplifier"
REPO_ID = "Ronak0/rti-pdf-simplifier"
print("1. Optimizing weights to float16...")
model = AutoModelForSeq2SeqLM.from_pretrained(LOCAL_DIR).half()
model.save_pretrained(LOCAL_DIR)
print("2. Generating valid configuration...")
config = AutoConfig.from_pretrained("google/flan-t5-base")
config.save_pretrained(LOCAL_DIR)
print(f"3. Uploading to Hugging Face Model Hub ({REPO_ID})...")
api = HfApi()
api.create_repo(repo_id=REPO_ID, repo_type="model", exist_ok=True)
api.upload_folder(
folder_path=LOCAL_DIR,
repo_id=REPO_ID,
repo_type="model",
)
print("Upload completed successfully.") |