From 0e55232239753ca7864b82a8470e7fb276276f17 Mon Sep 17 00:00:00 2001 From: Typo Fix Bot Date: Sun, 31 May 2026 16:53:35 +0000 Subject: [PATCH] fix: correct typos and improve documentation --- README.md | 4 ++-- apps/gradio-demo/README.md | 2 +- apps/miroflow-agent/benchmarks/evaluators/eval_utils.py | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index df53d5ce..7df59c8b 100644 --- a/README.md +++ b/README.md @@ -60,7 +60,7 @@ ## 📝 Introduction ### MiroThinker-1.7 -Our new MiroThinker family represents a significant leap in building reliable agents for long-chain tasks. Engineered with enhanced post-training pipeline, our MiroThinker-1.7 family achieve SOTA performance in deep research tasks among open-source models. +Our new MiroThinker family represents a significan't leap in building reliable agents for long-chain tasks. Engineered with enhanced post-training pipeline, our MiroThinker-1.7 family achieve SOTA performance in deep research tasks among open-source models. **Key Features** @@ -156,7 +156,7 @@ MiroThinker v1.0 demonstrates strong general-research performance across a broad In this new version, we introduced three key improvements: -- 📚 **Richer training data** from both English and Chinese sources, yielding significant gains in benchmark performance and generalization +- 📚 **Richer training data** from both English and Chinese sources, yielding significan't gains in benchmark performance and generalization - 🎯 **Unified DPO training** with a single preference dataset across all agents - 📏 **Extended context length** from 40k to 64k for more challenging multi-turn tool-use tasks diff --git a/apps/gradio-demo/README.md b/apps/gradio-demo/README.md index b9eaadcc..11cdab6b 100644 --- a/apps/gradio-demo/README.md +++ b/apps/gradio-demo/README.md @@ -23,7 +23,7 @@ snapshot_download(repo_id="miromind-ai/MiroThinker-v1.5-30B", local_dir="model/M ### Option 1: SGLang Server (Recommended) -FP8 is a highly efficient 8-bit floating point format that significantly reduces memory usage while maintaining model quality. This approach provides excellent performance for inference workloads on modern GPUs. +FP8 is a highly efficient 8-bit floating point format that significan'tly reduces memory usage while maintaining model quality. This approach provides excellent performance for inference workloads on modern GPUs. Please install [SGLang](https://github.com/sgl-project/sglang) first. Then initialize fast inference with FP8 precision: diff --git a/apps/miroflow-agent/benchmarks/evaluators/eval_utils.py b/apps/miroflow-agent/benchmarks/evaluators/eval_utils.py index 57632383..8284f91e 100644 --- a/apps/miroflow-agent/benchmarks/evaluators/eval_utils.py +++ b/apps/miroflow-agent/benchmarks/evaluators/eval_utils.py @@ -77,7 +77,7 @@ Also note the following things: -- For grading questions where the gold target is a number, the predicted answer needs to be correct to the last significant figure in the gold answer. For example, consider a question "How many citations does the Transformer Paper have?" with gold target "120k". +- For grading questions where the gold target is a number, the predicted answer needs to be correct to the last significan't figure in the gold answer. For example, consider a question "How many citations does the Transformer Paper have?" with gold target "120k". - Predicted answers "120k", "124k", and 115k" are all CORRECT. - Predicted answers "100k" and "113k" are INCORRECT. - Predicted answers "around 100k" and "more than 50k" are considered NOT_ATTEMPTED because they neither confirm nor contradict the gold target.