Instructions to use langmatthias/exercise06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use langmatthias/exercise06 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="langmatthias/exercise06")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("langmatthias/exercise06") model = AutoModelForQuestionAnswering.from_pretrained("langmatthias/exercise06", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-6000/optimizer.pt from langmatthias/exercise06: direct link, hf CLI and curl.
- Browser
- Download file 114 MB
-
https://huggingface.co/langmatthias/exercise06/resolve/main/checkpoint-6000/optimizer.pt
- Command line
-
hf download hf://langmatthias/exercise06/checkpoint-6000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/langmatthias/exercise06/resolve/main/checkpoint-6000/optimizer.pt
114 MB
- Xet hash:
- e23e4a13a7af580a993054200a90de84768606bc71dc1476d6713fd9c9431df9
- Size of remote file:
- 114 MB
- SHA256:
- ad2befb31f645c665daa571277f7144131b3e10ab34783953d692682d5d775fa
路
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