Update README.md

README.md

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----
-license: apache-2.0
----
+---
+tags:
+- text-generation
+- agent
+- tool-use
+- long-context
+license: other
+language:
+- en
+pipeline_tag: text-generation
+---
+
+# LIMI: Less is More for Agency
+
+## 📌 Table of Contents
+- [Overview](#overview)
+- [Model Details](#model-details)
+- [Dataset](#dataset)
+- [Quick Start](#quick-start)
+- [Prompting](#prompting)
+- [Evaluation](#evaluation)
+- [Limitations](#limitations)
+- [License](#license)
+- [Citation](#citation)
+
+## Overview
+
+LIMI is an agentic model fine‑tuned from GLM‑4.5 (355B) using compact, high‑quality data to emphasize:
+
+- Targeted capabilities: tool use, multi‑turn correction, spec compliance
+- Long‑context reasoning with tokenizer‑filtered samples (≤128k tokens)
+- OpenAI‑style `messages` with optional function/tool calls
+
+## Model Details
+
+- Base model: `zai-org/GLM-4.5`
+- Context: up to 128k tokens (training budget)
+- Training framework: slime
+- Training data: curated conversations from [GAIR/limi](https://huggingface.co/datasets/GAIR/limi)
+
+## Key Results
+ 
+| Model | Agency Bench FTFC | Agency Bench SR | Agency Bench RC | Training Samples |
+|-------|--------|---------|---------|-----------------|
+| LIMI (Ours) | **71.7** | **74.2** |**74.6**| 78 |
+| GLM-4.5 | 37.8 | 50.0 | 47.4 | 100k+ |
+
+## Model Zoo
+
+Our LIMO model is available on Hugging Face 🤗:
+
+| Model | Backbone | Size | Link |
+|---|---|---|---|
+| LIMI | [GLM‑4.5](https://huggingface.co/zai-org/GLM-4.5) | 355B | https://huggingface.co/GAIR/LIMI |
+| LIMI‑Air | [GLM‑4.5‑Air](https://huggingface.co/zai-org/GLM-4.5-Air) | 106B | https://huggingface.co/GAIR/LIMI-Air |
+
+
+## Datasets
+
+We release our datasets through Hugging Face 🤗:
+- Name: `GAIR/LIMI`
+- Summary: curated agentic SFT data (OpenAI `messages`, optional `tools`, normalized tool‑call arguments), filtered by tokenizer to ≤128k tokens; current release contains ~78 high‑quality samples.
+- Link: https://huggingface.co/datasets/GAIR/LIMI
+
+## Quick Start
+
+<details>
+<summary>Start with HF Transformers</summary>
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "GAIR/LIMI", torch_dtype="auto", device_map="auto", trust_remote_code=True
+)
+tok = AutoTokenizer.from_pretrained("GAIR/LIMI", trust_remote_code=True)
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant tasked with discovering mathematical function structures for scientific systems."},
+    {"role": "user", "content": "Modify the equation.py function, considering the physical meaning and relationships of the inputs."}
+]
+
+text = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tok(text, return_tensors="pt").to(model.device)
+out = model.generate(
+    **inputs,
+    max_new_tokens=4096,
+    temperature=0.6,
+    top_p=0.95,
+    do_sample=True,
+)
+print(tok.decode(out[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True))
+```
+
+</details>
+
+<details>
+<summary>Start with VLLM</summary>
+
+```python
+from vllm import LLM, SamplingParams
+from transformers import AutoTokenizer
+
+llm = LLM(model="GAIR/LIMI", trust_remote_code=True)
+tok = AutoTokenizer.from_pretrained("GAIR/LIMI", trust_remote_code=True)
+text = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+out = llm.generate(text, SamplingParams(temperature=0.6, max_tokens=4096, top_p=0.95))
+print(out[0].outputs[0].text)
+```
+
+</details>
+
+## Prompting
+
+- Messages follow OpenAI chat format; include a grounding system message when helpful.
+- Example:
+
+```json
+[
+  {"role": "system", "content": "You are a helpful assistant tasked with discovering mathematical function structures for scientific systems."},
+  {"role": "user", "content": "Modify the equation.py function, considering the physical meaning and relationships of the inputs."}
+]
+```
+
+## Evaluation
+
+- We report FTFC (First‑Turn Functional Completeness), SR@R (Success Rate at R), and RC@R (Remaining Chances at R) with R=3.
+- See the paper for experimental protocol and scores.
+
+## Limitations
+
+- May produce incorrect tool arguments or overfit to frequent schemas
+- Not safety‑filtered for sensitive domains; use with guardrails and oversight
+
+## License
+
+- Inherits base model (GLM‑4.5) terms; verify upstream license before deployment
+
+## Citation
+
+```bibtex
+@article{LIMI2025,
+  title   = {Less is More for Agentic Intelligence},
+  author  = {LIMI Authors},
+  year    = {2025},
+  journal = {arXiv preprint arXiv:2502.03387}
+}
+```
+