Instructions to use LiquidAI/LFM2.5-Encoder-230M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiquidAI/LFM2.5-Encoder-230M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="LiquidAI/LFM2.5-Encoder-230M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("LiquidAI/LFM2.5-Encoder-230M", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("LiquidAI/LFM2.5-Encoder-230M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from LiquidAI/LFM2.5-Encoder-230M: direct link, hf CLI and curl.
- Browser
- Download file 4.73 MB
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https://huggingface.co/LiquidAI/LFM2.5-Encoder-230M/resolve/main/tokenizer.json
- Command line
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hf download hf://LiquidAI/LFM2.5-Encoder-230M/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/LiquidAI/LFM2.5-Encoder-230M/resolve/main/tokenizer.json
4.73 MB
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