Instructions to use LiquidAI/LFM2.5-Encoder-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiquidAI/LFM2.5-Encoder-350M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="LiquidAI/LFM2.5-Encoder-350M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("LiquidAI/LFM2.5-Encoder-350M", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("LiquidAI/LFM2.5-Encoder-350M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4180ec7eea9e08f95430b0678ce78516c026490481bc29663bb277e5e2e9cfa5
- Size of remote file:
- 1.42 GB
- SHA256:
- cd70e404c3c6c1756b2cf5dc75de2a87788b460e3a6156c1a4ab134b824c2706
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