Instructions to use gabrielbianchin/base_esm2_t30_long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielbianchin/base_esm2_t30_long with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gabrielbianchin/base_esm2_t30_long")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gabrielbianchin/base_esm2_t30_long") model = AutoModelForMaskedLM.from_pretrained("gabrielbianchin/base_esm2_t30_long", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
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README.md
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---
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title: "ESM2 Quantized Base"
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---
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## ESM2 Quantized Base
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This is the base model for T30 quantized model. To use the quantized model, access [gabrielbianchin/esm2_t30_long_int4](https://huggingface.co/gabrielbianchin/esm2_t30_long_int4).
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