Instructions to use gabrielbianchin/base_esm2_t12_long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielbianchin/base_esm2_t12_long with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gabrielbianchin/base_esm2_t12_long")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gabrielbianchin/base_esm2_t12_long") model = AutoModelForMaskedLM.from_pretrained("gabrielbianchin/base_esm2_t12_long", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| title: "ESM2 Long and Quantized Base" | |
| ## ESM2 Quantized Base | |
| This is the base model for T12 quantized model. To use the quantized model, access [gabrielbianchin/esm2_t12_long_int4](https://huggingface.co/gabrielbianchin/esm2_t12_long_int4): |