Instructions to use prajwalJumde/test111 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajwalJumde/test111 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="prajwalJumde/test111")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("prajwalJumde/test111") model = AutoModelForQuestionAnswering.from_pretrained("prajwalJumde/test111", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from prajwalJumde/test111: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/prajwalJumde/test111/resolve/main/tokenizer.json
- Command line
-
hf download hf://prajwalJumde/test111/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/prajwalJumde/test111/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 1322b4e556046255c59915017e0edc8d0d9d118388786e6658595ea63b82d0be
- Size of remote file:
- 17.1 MB
- SHA256:
- da0622cea7b6d2fd81dcd20fd6816f8d0ff407f2677819e942bb5889d026c9a3
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.