初始化项目，由ModelHub XC社区提供模型

Model: squ11z1/Mythos-nano Source: Original Platform
2026-07-10 20:49:00 +08:00
commit a6d9ccde36
19 changed files with 322 additions and 0 deletions
--- a/README.md
+++ b/README.md
@@ -0,0 +1,89 @@
+---
+license: mit
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- reasoning
+- math
+- code
+- qwen2
+- mythos-nano
+base_model:
+- WeiboAI/VibeThinker-3B
+base_model_relation: finetune
+---
+> Mythos-nano tool-calling is coming, but check out Merlin-Agent!
+    https://huggingface.co/Merlin-Research/Merlin-Agent
+
+![Gemini_Generated_Image_jna8spjna8spjna8](https://cdn-uploads.huggingface.co/production/uploads/67329d3f69fded92d56ab41a/5CeYH1uT1Jkmx7LoBtoQF.png)
+
+  </a>
+  
+> **Disclaimer:** This is **not** an official release by Anthropic.  
+> Mythos-nano is an independent open model project.
+
+# Mythos-nano
+
+![Gemini_Generated_Image_1nl8n11nl8n11nl8](https://cdn-uploads.huggingface.co/production/uploads/67329d3f69fded92d56ab41a/Jbqo3kdC08nA4lt1Oli_z.png)
+
+<blockquote style="border-left: 4px solid #ff6b6b; background-color: #fff5f5; padding: 10px 15px; margin: 10px 0; color: #cc3333;">
+    <span style="font-weight: bold;">🚨 </span> This model was not trained on tool-calling or agent-based programming data. We therefore do not recommend using it for tasks that involve function calling, API orchestration, or autonomous coding agents.
+For programming tasks, we recommend using this model on competitive programming problems (e.g., LeetCode-style) - Weibo Lab.
+</blockquote>
+
+<blockquote style="border-left: 4px solid #ff6b6b; background-color: #fff5f5; padding: 10px 15px; margin: 10px 0; color: #cc3333;">
+    <span style="font-weight: bold;">⚠️ </span> Abliterated (uncensored): the refusal direction has been removed, so this model will not decline requests a safety-tuned model normally would. Safety guardrails are reduced — use responsibly and at your own risk; you are solely responsible for outputs and legal compliance.
+</blockquote>
+
+## 🏆 Benchmarks
+
+![ChatGPT Image Jun 19, 2026 at 12_53_05 PM](https://cdn-uploads.huggingface.co/production/uploads/67329d3f69fded92d56ab41a/6i8nAQqTS1bZjwR9gSNIq.png)
+
+### Full comparison (mathematics · coding · knowledge · instruction)
+
+| Model | Params | AIME25 | AIME26 | HMMT25 | BruMO25 | IMO-Ans | LCBv6 | OJBench | GPQA-D | IFEval | IFBench |
+|---|---|---|---|---|---|---|---|---|---|---|---|
+| Kimi K2.5 | 1T | 96.1 | 93.3 | 95.4 | 98.3 | 81.8 | 85.0 | 54.7 | 87.6 | 93.9 | 70.0 |
+| GLM-5 | 744B | 96.7 | 95.8 | 97.9 | – | 82.5 | 85.5 | 55.0 | 86.0 | 92.6 | 76.5 |
+| DeepSeek V3.2 | 671B | 93.1 | 94.2 | 90.2 | 96.7 | 78.3 | 80.8 | 48.4 | 82.4 | 92.6 | 60.7 |
+| Gemini 3 Pro | N/A | 96.0 | 91.7 | 97.5 | 98.3 | 83.1 | 87.4 | 58.8 | 91.9 | – | 70.4 |
+| Claude Opus 4.5 | N/A | 92.8 | 95.1 | 92.9 | – | 78.5 | 84.8 | – | 87.0 | – | 58.0 |
+| GPT-5 (high) | N/A | 94.6 | – | 88.3 | 91.7 | 76.0 | 84.5 | – | 85.7 | – | 73.1 |
+| **Mythos-nano** | **3B** | **91.4** | **94.3** | **89.3** | **93.8** | **76.4** | **80.2** | **38.6** | **70.2** | **93.4** | **74.5** |
+| **Mythos-nano + CLR** | **3B** | **96.7** | **97.1** | **95.4** | **99.2** | **80.6** | – | – | **72.9** | – | – |
+
+### LeetCode contests (Python, pass-rate)
+
+| Model | Aggregate |
+|---|---|
+| GPT-5.3-Codex | 100.0% (128/128) |
+| Gemini 3.1 Pro | 99.2% (127/128) |
+| Gemini 3 Flash | 96.9% (124/128) |
+| **Mythos-nano** | **96.1% (123/128)** |
+| GPT-5.2 | 95.3% (122/128) |
+| Qwen3-Max | 91.4% (117/128) |
+| Kimi K2.5 | 90.6% (116/128) |
+| Claude Opus 4.6 | 86.7% (111/128) |
+
+A 3B model placing within ~4 points of trillion-parameter systems on competition math
+and live code — the core thesis: with verifiable feedback, small models reach frontier
+reasoning.
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+tok = AutoTokenizer.from_pretrained("squ11z1/Mythos-nano")
+model = AutoModelForCausalLM.from_pretrained("squ11z1/Mythos-nano", dtype=torch.bfloat16, device_map="cuda")
+msgs = [{"role": "user", "content": "Find all integer solutions of x^2 - y^2 = 12."}]
+ids = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt").to("cuda")
+print(tok.decode(model.generate(ids, max_new_tokens=2048, temperature=0.6)[0], skip_special_tokens=True))
+```
+Recommended sampling: temperature **0.6–1.0**, up to **40960** output tokens for hard problems.
+
+## GGUF
+`mythos-nano-f16.gguf` and `mythos-nano-Q4_K_M.gguf` are provided for llama.cpp / Ollama.
+
+## License
+MIT.