Instructions to use postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq") model = AutoModelForMaskedLM.from_pretrained("postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq/resolve/main/training_args.bin
- Command line
-
hf download hf://postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- be92b097a3b6f0917820644acceb935c07ad6c1262ae154b98817f383931d310
- Size of remote file:
- 3.9 kB
- SHA256:
- 81e137c88dedc1030ac71e651025cec0809baeccb47af69a01c380ad639c71b3
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