Text Generation
PEFT
Safetensors
English
astrophysics
orbital-mechanics
cosmology
celestial-mechanics
lora
vigyan-ai
conversational
Instructions to use shreyansh12183/olmo2-7b-astro-logic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shreyansh12183/olmo2-7b-astro-logic with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-1124-7B-Instruct") model = PeftModel.from_pretrained(base_model, "shreyansh12183/olmo2-7b-astro-logic") - Notebooks
- Google Colab
- Kaggle
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Download eval_report.md from shreyansh12183/olmo2-7b-astro-logic: direct link, hf CLI and curl.
- Browser
- Download file 1.34 kB
-
https://huggingface.co/shreyansh12183/olmo2-7b-astro-logic/resolve/main/eval_report.md
- Command line
-
hf download hf://shreyansh12183/olmo2-7b-astro-logic/eval_report.md
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curl -L -o eval_report.md https://huggingface.co/shreyansh12183/olmo2-7b-astro-logic/resolve/main/eval_report.md
1.34 kB
| license: apache-2.0 | |
| base_model: allenai/OLMo-2-1124-7B-Instruct | |
| tags: | |
| - stem | |
| - mathematics | |
| - olympiad-physics | |
| - qlora | |
| - unsloth | |
| - trl | |
| - 4-bit | |
| pipeline_tag: text-generation | |
| # Specialist 1: OLMo-2-13B Pure Astronomy & Scientific Logic | |
| ## Model Summary | |
| - **Base Architecture:** `allenai/OLMo-2-1124-7B-Instruct` | |
| - **Quantization:** 4-bit NormalFloat4 (NF4) with Double Quantization (`BitsAndBytesConfig`) | |
| - **LoRA Configuration:** $r=64$, $\alpha=128$, dropout=0.05, 7 linear projection targets (`q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj`) | |
| - **Loss Masking:** Prompt loss masking (`train_on_inputs: false`) via `DataCollatorForCompletionOnlyLM` | |
| - **Training Datasets:** `shreyansh12183/qwen-72b-sovereign-stem-master-500k` (Math/Physics) + `allenai/tulu-3-sft-mixture` | |
| - **Target Repository:** `shreyansh12183/olmo2-7b-astro-logic` (100% PRIVATE 🔒) | |
| ## Live 5-Prompt Benchmark Results | |
| | # | Domain / Problem | Status | | |
| |---|------------------|--------| | |
| | 1 | Keplers Third Law Derivation | PASSED | | |
| | 2 | Schwarzschild Horizon | PASSED | | |
| | 3 | Resolution Inference Proof | PASSED | | |
| | 4 | Hubble Expansion Formulation | PASSED | | |
| | 5 | Halting Problem Undecidability | PASSED | | |
| ## Zero Cloud Spend Compliance | |
| - Trained 100% on Kaggle Dual Tesla T4 GPUs (`NvidiaTeslaT4x2`). | |
| - **AWS Spend:** $0.00. | |