Text Classification
Transformers
Safetensors
yield-weather-soil
crop-yield
multi-temporal
regression
yield-estimation
custom_code
Instructions to use ICICLE-AI/yield-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ICICLE-AI/yield-estimation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ICICLE-AI/yield-estimation", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("ICICLE-AI/yield-estimation", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Delete config.json
Browse files- config.json +0 -184
config.json
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{
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"K": 22,
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"S": 24,
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"W": 22,
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"architectures": [
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"YieldForRegression"
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],
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"crop_emb_dim": 8,
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"d_model": 64,
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"dim_ff": 128,
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"dropout": 0.4,
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"dtype": "float32",
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],
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"model_type": "yield-weather-soil",
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"nhead": 4,
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"num_layers": 4,
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"pool": "last",
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"ph",
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"om",
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"cec",
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"awc",
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"clay",
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"p_ppm",
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"k_ppm",
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"mg_ppm",
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"ca_ppm",
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"k_te",
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"mg_te",
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"ca_te",
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"s_ppm",
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"zn_ppm",
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"fe_ppm",
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"mn_ppm",
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"cu_ppm",
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"b_ppm",
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"na_ppm",
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"sand",
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"silt",
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"bd",
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"elevation",
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"slope"
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],
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"auto_map": {
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"AutoConfig": "configuration_yield.YieldConfig",
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"AutoModel": "modeling_yield.YieldForRegression"
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},
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"custom_pipelines": {
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"yield-estimation": {
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"impl": "pipeline_yield.YieldEstimationPipeline",
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"pt": [
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"AutoModel"
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