import json import requests API_URL = "https://api-inference.huggingface.co/models/formermagic/roberta-base-python-1m" headers = {"Authorization": f"Bearer {API_TOKEN}"} def query(payload): data = json.dumps(payload) response = requests.request("POST", API_URL, headers=headers, data=data) return json.loads(response.content.decode("utf-8")) data = query({"inputs": "The answer to the universe is <mask>."})
Select the task you want to fine-tune the model on
Launch training from a local machine or inside AWS ?
from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("formermagic/roberta-base-python-1m") model = AutoModelForMaskedLM.from_pretrained("formermagic/roberta-base-python-1m")
git lfs install git clone https://huggingface.co/formermagic/roberta-base-python-1m
# if you want to clone without large files – just their pointers # prepend your git clone with the following env var: GIT_LFS_SKIP_SMUDGE=1
<mask>
