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)# pip install -U transformers accelerate # 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 special_tokens_map.json from LiquidAI/LFM2.5-Encoder-230M: direct link, hf CLI and curl.
- Browser
- Download file 120 Bytes
-
https://huggingface.co/LiquidAI/LFM2.5-Encoder-230M/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://LiquidAI/LFM2.5-Encoder-230M/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/LiquidAI/LFM2.5-Encoder-230M/resolve/main/special_tokens_map.json
120 Bytes
| { | |
| "bos_token": "<|startoftext|>", | |
| "eos_token": "<|im_end|>", | |
| "mask_token": "<|mask|>", | |
| "pad_token": "<|pad|>" | |
| } | |