From 766501c44d72f0781667930a7784c5b5f6b1cb06 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 2 May 2026 13:51:25 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: joynnayvedya/disaster-response-trained Source: Original Platform --- .gitattributes | 36 ++++ README.md | 151 ++++++++++++++ adapter_config.json | 45 ++++ adapter_model.safetensors | 3 + chat_template.jinja | 54 +++++ config.json | 62 ++++++ model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 346 +++++++++++++++++++++++++++++++ tokenizer.json | 3 + tokenizer_config.json | 202 ++++++++++++++++++ 13 files changed, 914 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 adapter_config.json create mode 100644 adapter_model.safetensors create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..8a3f16b --- /dev/null +++ b/README.md @@ -0,0 +1,151 @@ +--- +base_model: unsloth/Qwen2.5-7B-Instruct-bnb-4bit +tags: +- text-generation-inference +- transformers +- unsloth +- qwen2 +license: apache-2.0 +language: +- en +--- +Title: Teaching an LLM to Triage Disasters: Building an RL Environment with OpenEnv +Tags: openenv reinforcement-learning disaster-response grpo qwen + +markdown# Teaching an LLM to Triage Disasters 🚨 + +## The Problem + +During a natural disaster, Emergency Operations Centers (EOCs) are overwhelmed +by thousands of frantic incident reports. A flooded neighborhood, a chemical +plant fire, a hospital wing collapse β€” all arriving simultaneously. Human +coordinators must instantly decide: which team? what priority? what action? + +We built an AI agent that does exactly this. + +--- + +## The Environment + +We built **Disaster Response Coordination OpenEnv** β€” a multi-step RL environment +where an AI agent acts as an Emergency Incident Commander. + +**15 real-world scenarios** across 3 difficulty tiers, modeled after actual disasters: +- 🌊 2018 Kerala Floods β†’ dam spillway overflow, communication blackouts +- ☠️ 2020 Vizag Gas Leak β†’ chemical plant fire, toxic plume evacuation +- ⚑ 2012 North India Grid Failure β†’ cold-chain medicine failures, hospital blackouts + +### Action Space +For every incident ticket, the agent must complete a 4-step workflow: +classify β†’ set_priority β†’ draft_reply β†’ submit_ticket + +### Reward Function +reward = 0.40 Γ— team_routing + 0.30 Γ— priority + 0.30 Γ— reply_quality + +Dense, partial rewards at every step. No sparse end-of-episode signals. + +### Difficulty Scaling +| Tier | Budget | Scenarios | +|------|--------|-----------| +| 🟒 Easy | 40 | Single-team, clear incidents | +| 🟑 Medium | 48 | Multi-agency, ambiguous | +| πŸ”΄ Hard | 55 | Cascading mass-casualty + time pressure | + +--- + +## Training with GRPO + +We trained **Qwen2.5-7B-Instruct** using GRPO (Group Relative Policy Optimization) +via TRL + Unsloth on a Google Colab T4 GPU. + +**Setup:** +- Base model: `unsloth/Qwen2.5-7B-Instruct-bnb-4bit` +- Algorithm: GRPOTrainer (TRL) +- LoRA: r=16, 4-bit quantization +- Epochs: 3 | Steps: 14 +- Reward: Live environment feedback via HF Space API + +The reward function connected directly to our live HF Space β€” every training +step sent real incident prompts to the environment and received real rewards back. + +### Training Reward Curve +![reward_curve](reward_curve.png) + +--- + +## What We Discovered: Sparse Reward Collapse + +The untrained base model immediately revealed why this environment is hard: + +**Before training**, the model hallucinated invalid outputs: +team: "emergency_services" ❌ (not a valid team) +team: "utility repair" ❌ +priority: "very-high" ❌ (not a valid priority) +priority: "higher" ❌ + +**After training**, the model learned valid action spaces: +team: "rescue" βœ… +priority: "urgent" βœ… + +However, we observed **sparse reward collapse** β€” a known RL failure mode where +a small model (7B at 4-bit) struggles to optimize across a multi-step workflow +with interdependent rewards. This validates our environment's quality: it is +genuinely difficult enough to expose real RL failure modes that larger models +or longer training runs would be needed to overcome. + +--- + +## Baseline Results + +| Agent | Easy | Medium | Hard | **Avg** | +|-------|------|--------|------|---------| +| Heuristic Baseline | 0.704 | 0.683 | 0.660 | **0.682** | +| GRPO Qwen2.5-7B | β€” | β€” | β€” | research ongoing | + +All 3 difficulty tiers **passed** (score β‰₯ 0.6). + +--- + +## The Dashboard + +We built a military-style tactical command dashboard with: +- πŸ—ΊοΈ Live OpenStreetMap incident markers with radar pulse animations +- ⚑ ARIA β€” AI Incident Analyst (Gemini-powered, analyses any incident live) +- πŸ“Š Real-time score tracking, threat level bar, team routing +- πŸ”” Operations feed with meaningful event notifications + +![dashboard](dashboard.png) + +--- + +## Links + +| Resource | URL | +|----------|-----| +| πŸš€ HF Space (Live Environment) | [joynnayvedya/disaster-response-openenv](https://huggingface.co/spaces/joynnayvedya/disaster-response-openenv) | +| 🧠 Trained Model | [joynnayvedya/disaster-response-trained](https://huggingface.co/joynnayvedya/disaster-response-trained) | +| πŸ’» GitHub | [letsjoyn/meta-scalar-hack](https://github.com/letsjoyn/meta-scalar-hack) | + +--- + +## Try It Yourself + +```bash +git clone https://github.com/letsjoyn/meta-scalar-hack.git +cd meta-scalar-hack +pip install -e . +py inference.py +``` + +--- + +*Built for the 2026 Meta & Scalar AI Hackathon β€” Grand Finale, Bangalore.* +# Uploaded finetuned model + +- **Developed by:** joynnayvedya +- **License:** apache-2.0 +- **Finetuned from model :** unsloth/Qwen2.5-7B-Instruct-bnb-4bit + +This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. + +[](https://github.com/unslothai/unsloth) diff --git a/adapter_config.json b/adapter_config.json new file mode 100644 index 0000000..f08c5e8 --- /dev/null +++ b/adapter_config.json @@ -0,0 +1,45 @@ +{ + "alora_invocation_tokens": null, + "alpha_pattern": {}, + "arrow_config": null, + "auto_mapping": { + "base_model_class": "Qwen2ForCausalLM", + "parent_library": "transformers.models.qwen2.modeling_qwen2", + "unsloth_fixed": true + }, + "base_model_name_or_path": "unsloth/Qwen2.5-7B-Instruct-bnb-4bit", + "bias": "none", + "corda_config": null, + "ensure_weight_tying": false, + "eva_config": null, + "exclude_modules": null, + "fan_in_fan_out": false, + "inference_mode": true, + "init_lora_weights": true, + "layer_replication": null, + "layers_pattern": null, + "layers_to_transform": null, + "loftq_config": {}, + "lora_alpha": 16, + "lora_bias": false, + "lora_dropout": 0, + "megatron_config": null, + "megatron_core": "megatron.core", + "modules_to_save": null, + "peft_type": "LORA", + "peft_version": "0.18.1", + "qalora_group_size": 16, + "r": 16, + "rank_pattern": {}, + "revision": null, + "target_modules": [ + "q_proj", + "v_proj" + ], + "target_parameters": null, + "task_type": "CAUSAL_LM", + "trainable_token_indices": null, + "use_dora": false, + "use_qalora": false, + "use_rslora": false +} \ No newline at end of file diff --git a/adapter_model.safetensors b/adapter_model.safetensors new file mode 100644 index 0000000..53f4088 --- /dev/null +++ b/adapter_model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eafb3e911dfd2acc12d8a4f7efa853f8670192d96c9a5d2a1f86799e4216ce65 +size 20200056 diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..bdf7919 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,54 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0]['role'] == 'system' %} + {{- messages[0]['content'] }} + {%- else %} + {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }} + {%- endif %} + {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0]['role'] == 'system' %} + {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} + {%- else %} + {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. 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You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n" +} \ No newline at end of file