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)# 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
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| "S": 66, | |
| "W": 6, | |
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| "YieldForSequenceClassification" | |
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| "model_type": "yield-weather-soil", | |
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| "num_layers": 4, | |
| "pool": "last", | |
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| "cec_mean_0-5cm", | |
| "cec_mean_5-15cm", | |
| "cec_mean_15-30cm", | |
| "cec_mean_30-60cm", | |
| "cec_mean_60-100cm", | |
| "cec_mean_100-200cm", | |
| "cfvo_mean_0-5cm", | |
| "cfvo_mean_5-15cm", | |
| "cfvo_mean_15-30cm", | |
| "cfvo_mean_30-60cm", | |
| "cfvo_mean_60-100cm", | |
| "cfvo_mean_100-200cm", | |
| "clay_mean_0-5cm", | |
| "clay_mean_5-15cm", | |
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| "clay_mean_30-60cm", | |
| "clay_mean_60-100cm", | |
| "clay_mean_100-200cm", | |
| "nitrogen_mean_0-5cm", | |
| "nitrogen_mean_5-15cm", | |
| "nitrogen_mean_15-30cm", | |
| "nitrogen_mean_30-60cm", | |
| "nitrogen_mean_60-100cm", | |
| "nitrogen_mean_100-200cm", | |
| "ocd_mean_0-5cm", | |
| "ocd_mean_5-15cm", | |
| "ocd_mean_15-30cm", | |
| "ocd_mean_30-60cm", | |
| "ocd_mean_60-100cm", | |
| "ocd_mean_100-200cm", | |
| "ocs_mean_0-5cm", | |
| "ocs_mean_5-15cm", | |
| "ocs_mean_15-30cm", | |
| "ocs_mean_30-60cm", | |
| "ocs_mean_60-100cm", | |
| "ocs_mean_100-200cm", | |
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| "phh2o_mean_15-30cm", | |
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| "phh2o_mean_60-100cm", | |
| "phh2o_mean_100-200cm", | |
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| "sand_mean_5-15cm", | |
| "sand_mean_15-30cm", | |
| "sand_mean_30-60cm", | |
| "sand_mean_60-100cm", | |
| "sand_mean_100-200cm", | |
| "silt_mean_0-5cm", | |
| "silt_mean_5-15cm", | |
| "silt_mean_15-30cm", | |
| "silt_mean_30-60cm", | |
| "silt_mean_60-100cm", | |
| "silt_mean_100-200cm", | |
| "soc_mean_0-5cm", | |
| "soc_mean_5-15cm", | |
| "soc_mean_15-30cm", | |
| "soc_mean_30-60cm", | |
| "soc_mean_60-100cm", | |
| "soc_mean_100-200cm" | |
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| 32, | |
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| 48, | |
| 52 | |
| ], | |
| "transformers_version": "5.13.0", | |
| "use_crop": true, | |
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| "y_mean": 166.3075714111328, | |
| "y_std": 30.291048049926758, | |
| "problem_type": "regression", | |
| "num_labels": 1, | |
| "id2label": { | |
| "0": "YIELD_BU_ACRE" | |
| }, | |
| "label2id": { | |
| "YIELD_BU_ACRE": 0 | |
| }, | |
| "tokenizer_class": "YieldTokenizer", | |
| "auto_map": { | |
| "AutoConfig": "configuration_yield.YieldConfig", | |
| "AutoModelForSequenceClassification": "modeling_yield.YieldForSequenceClassification", | |
| "AutoTokenizer": [ | |
| "tokenization_yield.YieldTokenizer", | |
| null | |
| ] | |
| } | |
| } |