Instructions to use InstaDeepAI/nucleotide-transformer-500m-human-ref with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-500m-human-ref with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-500m-human-ref")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref") model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
75aa8a4
1
Parent(s): 28d7fac
Add TF weights
Browse filesModel converted by the [`transformers`' `pt_to_tf` CLI](https://github.com/huggingface/transformers/blob/main/src/transformers/commands/pt_to_tf.py). All converted model outputs and hidden layers were validated against its PyTorch counterpart.
Maximum crossload output difference=2.575e-05; Maximum crossload hidden layer difference=6.104e-05;
Maximum conversion output difference=2.575e-05; Maximum conversion hidden layer difference=6.104e-05;
CAUTION: The maximum admissible error was manually increased to 7e-05!
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:79815a9c5226b15242850af58e4bb3574d29230254642f5d547350e3e92b1aad
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size 1943319236
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