Text Generation
PEFT
Safetensors
English
Spanish
llama4_text
agriculture
climate
crop-calendar
evidence-grounding
bilingual
lora
autoscientist
adaption
conversational
4-bit precision
bitsandbytes
Instructions to use MarianaCodebase/AgroVeritas-Scout-17B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MarianaCodebase/AgroVeritas-Scout-17B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Llama-4-Scout-17B-16E-Instruct_bnb_4bit") model = PeftModel.from_pretrained(base_model, "MarianaCodebase/AgroVeritas-Scout-17B") - Notebooks
- Google Colab
- Kaggle
File size: 1,068 Bytes
612f22e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"release_model_id": "adaption_llama_4_scout_17b_16_agri_evidence_qa_158a7fd8",
"category": "Agriculture",
"evaluation_source": "Adaption AutoScientist held-out Agriculture category tasks",
"base_win_rate_percent": 23,
"adapted_win_rate_percent": 78,
"absolute_improvement_percentage_points": 55,
"relative_lift_percent": 239.1,
"adapted_to_base_ratio": 3.391,
"training": {
"global_steps": 159,
"epochs": 3,
"first_recorded_eval_loss": 0.756591796875,
"final_eval_loss": 0.682373046875
},
"data_quality": {
"same_run_score_before": 9.0,
"same_run_score_after": 10.0,
"same_run_relative_improvement_percent": 11.1,
"grade_before": "A",
"grade_after": "A",
"percentile_before": 43.9,
"percentile_after": 57.7
},
"claim_boundaries": [
"The held-out evaluator prompts are private and are not published.",
"The C-to-A result is a cross-version project development journey, not a same-run quality comparison.",
"The model release is the 158a7fd8 run; the 2329bca3 retry is excluded."
]
}
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