shreyansh12183/olmo2-7b-phd-pure-math

📐 OLMo-2 7B Pure Mathematics Specialist

A mathematical reasoning adapter fine-tuned on advanced proofs in Algebraic Topology, Differential Geometry, Abstract Algebra, and Real Analysis.

Developed by Shreyansh Singh to investigate rigorous symbolic reasoning in open-weight language models.

---

🔬 Capabilities

• Formal Proof Structuring: Step-by-step inductive, deductive, and contradiction-based mathematical arguments.
• Topology & Homology: Fundamental groups, homotopy equivalence, Mayer-Vietoris sequences, and manifold theory.
• Abstract Structures: Category theory, Galois theory, and commutative algebra.

💻 Quick Start & Loading in Python (PEFT LoRA)

This model is uploaded as a PEFT LoRA Adapter. To load and run inference in Python using transformers & peft:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model_id = "allenai/OLMo-2-1124-7B-Instruct"
adapter_id = "shreyansh12183/olmo2-7b-phd-pure-math"

# 1. Load Base Model & Tokenizer
tokenizer = AutoTokenizer.from_pretrained(base_model_id)
base_model = AutoModelForCausalLM.from_pretrained(
    base_model_id,
    torch_dtype=torch.float16,
    device_map="auto"
)

# 2. Attach LoRA Adapter
model = PeftModel.from_pretrained(base_model, adapter_id)

# 3. Generate Response
prompt = "Your prompt here..."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

🖥️ Running in LM Studio & Ollama (GGUF)

To run this model on laptops/macbooks using LM Studio, Ollama, or Jan.ai:

1. Download the merged GGUF version (available under shreyansh12183/ GGUF repos).
2. For Ollama, run:

   ollama run hf.co/shreyansh12183/olmo2-7b-phd-pure-math-GGUF:Q4_K_M
   

---

Developed by ExperimentLab AI | Official Website: https://experimentlab.in | Contact: shreyansh@experimentlab.in