Instructions to use Vydiant/mesh-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vydiant/mesh-pipeline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Vydiant/mesh-pipeline")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Vydiant/mesh-pipeline") model = AutoModel.from_pretrained("Vydiant/mesh-pipeline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Dennis Minn commited on
Commit ·
e87dead
1
Parent(s): 859160b
removed AutoModelForSequenceClassification and updated underlying model
Browse files- config.json +2 -4
config.json
CHANGED
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@@ -11,14 +11,12 @@
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"model": {
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"pt": [
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"DennisOneHealth/mesh-encoder",
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"
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]
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}
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},
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"impl": "mesh_pipeline.MeshPipeline",
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"pt": [
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"AutoModelForSequenceClassification"
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],
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"tf": [],
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"type": "text"
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}
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"model": {
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"pt": [
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"DennisOneHealth/mesh-encoder",
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"0b614be"
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]
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}
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},
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"impl": "mesh_pipeline.MeshPipeline",
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+
"pt": [],
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"tf": [],
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"type": "text"
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}
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