Open-source LLM and dataset for sports forecasting (Pro Golf)
Hey HN, I fine-tuned a small open-source model on golf forecasting and it beats GPT-5 at predicting golf outcomes. The same approach can be used to build a specialized model in any domain, you just need to update a few search queries. We fine-tuned gpt-oss-120b with LoRA on 3,178 golf forecasting questions, using GRPO with Brier score as the reward. Our model outperformed GPT-5 on Brier Skill (17% vs 12.8%) and ECE (6% vs 10.6%) on 855 held-out questions. How to try it: the model and dataset are open-source, with code, on Hugging Face. How to build your own specialized model: Update the…
Open-source LLM and dataset for sports forecasting (Pro Golf) launched on February 24, 2026 with 7 votes, #1,385 of 16,627 launches that month and more than 75% of that year's launches.
What it does
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Starting from nothing but 9 search queries, we used the Lightning Rod SDK to automatically generate 3,178 forecasting questions from news articles, label them using real outcomes, and train this model via RL. No expertise required. No manual labeling. No domain-specific engineering. The result beats GPT-5 on held-out questions. You can do this in any domain — just change the search queries. See how we built the dataset . This repo contains a LoRA adapter for gpt-oss-120b . A standalone merge.py script is included to merge it into a full model. Evaluated on 855 held-out test questions (temporal split, Aug 2025+). Brier Score : Mean squared error between predicted probability and outcome.…from huggingface.co
In the maker’s words, at launch
Hey HN, I fine-tuned a small open-source model on golf forecasting and it beats GPT-5 at predicting golf outcomes. The same approach can be used to build a specialized model in any domain, you just need to update a few search queries. We fine-tuned gpt-oss-120b with LoRA on 3,178 golf forecasting questions, using…
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LLM StatsOct 2025 · llm-stats.com · ▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
TensorZero2025 · github.com · ▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
Fine-tune an 8B model on a 4 GB laptop GPUAug 2026 · github.com · ▲139Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
Fully client-side GPT2 prediction visualizer2023 · perplexity.vercel.app · ▲153Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
- L2LoraLand – 25 fine-tuned LLMs that beat GPT-42024 · predibase.com · ▲24
Hi all, today we're excited to launch LoraLand: 25 fine-tuned mistral-7b models that outperform #gpt4 on task-specific applications ranging from sentiment detection to question answering. All 25 fine-tuned models… - Outperform GPT-4, GPT-3.5-turbo, and mistral-7b-instruct for specific tasks - Are cost-effectively served from a single GPU through LoRAX - Were trained for less than $8 each on average You can prompt all of the fine-tuned models today and compare their results to mistral-7b-instruct in real time! We'd love to hear comments and feedback from the community

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