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Model: OrdenWills/LFM2.5-350M-home-assistant-sft
Source: Original Platform

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README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: LiquidAI/LFM2.5-350M
+tags:
+- smart-home
+- home-automation
+- tool-calling
+- function-calling
+- iot
+- unsloth
+- lora
+- lfm2
+pipeline_tag: text-generation
+---
+
+# LFM2.5-350M Home Assistant (Stage 2 Stable Release)
+
+A purpose-trained smart home automation model fine-tuned from [LiquidAI/LFM2.5-350M](https://huggingface.co/LiquidAI/LFM2.5-350M). This model controls lights, doors, thermostats, TVs, fans, speakers, and home scenes through structured tool calls, with full awareness of current device states.
+
+**⚠️ Version Notice:** This is the **Stable Release**, trained exclusively on our robust Stage 2 State-Aware dataset (v13 Final Merge). The experimental multi-stage version is currently still in training and will be released for comparison once stabilized. 
+
+**👉 Which file should I download?**
+For the most stable experience right now, download one of the following GGUF files:
+* `LFM2.5-350M.F16.gguf`
+* `LFM2.5-350M.Q4_K_M.gguf` (Recommended for most users, best balance of speed and size)
+* `LFM2.5-350M.Q8_0.gguf` (Highest quality quantization)
+
+---
+
+## What It Does
+
+Given a natural language command and the current state of all connected devices, the model outputs the correct tool call — or explains in plain text why no action is needed. It handles:
+
+- **Advanced Device Disambiguation** — If you say "Turn off the TV", the model will intelligently resolve which TV you mean by checking if only one TV is connected, checking if you are in a room with a TV, or inferring intent from the state (e.g., if only one TV is currently ON, it turns that one off via a `<think>` trace).
+- **Media & Music Playback** — "Play Truth In The World By Lucky Dube" → `control_speaker(room='living_room', action='play', media='Truth In The World By Lucky Dube')`
+- **Direct commands** — "Turn on the bedroom light" → `toggle_lights(room='bedroom', state='on')`
+- **Already-satisfied detection** — "Turn on the bedroom light" when `bedroom:on` in STATE → "The bedroom light is already on." (no tool call)
+- **Pronoun resolution** — "Turn off the light" when `current_user_room=kitchen` → `toggle_lights(room='kitchen', state='off')`
+- **Bulk state-aware actions** — "Turn off what's on" → reads STATE, emits one call per lit room using `<think>` logic.
+- **Undo / repeat via action log** — "Undo that" + `[RECENT ACTIONS: toggle_lights(bedroom, on)]` → `toggle_lights(room='bedroom', state='off')`
+- **Multi-device compound commands** — "Lock the front door and turn off the living room light" → uses a rigid reasoning format (`Total: N tool calls required`) to emit parallel tool calls.
+- **Topology-aware rejection** — "Turn on the garage light" when garage not in connected rooms → `intent_unclear(reason='unsupported_device')`
+- **Scene activation** — "Movie night" / "Bedtime" / "I'm leaving" → `set_scene(...)`
+- **Fan control** — "Set the bedroom fan to high" → `control_fan(room='bedroom', state='on', speed='high')`
+- **Thermostat** — "Make it 72 degrees" → `set_thermostat(temperature=72, mode='heat')`
+- **Syntactic Action Triggers** — Internal reasoning strictly concludes with `ACTION REQUIRED.` or `ACTION NOT REQUIRED. Text reply only.` to reliably signal structural intent before opening a JSON block.
+
+---
+
+## Tool Schema
+
+The model outputs calls from the following 10-tool schema. All tools use exact parameter names.
+
+```python
+toggle_lights(room: str, state: 'on'|'off')
+# room: living_room | bedroom | kitchen | bathroom | office | hallway
+
+toggle_all_lights(state: 'on'|'off')
+
+lock_door(door: str, state: 'lock'|'unlock')
+# door: front | back | garage | side | bedroom | bathroom | office | kitchen | living_room
+
+lock_all_doors(state: 'lock'|'unlock')
+
+set_thermostat(temperature: int, mode: 'heat'|'cool'|'auto')
+# temperature range: 60–80°F
+
+set_scene(scene: 'movie_night'|'bedtime'|'morning'|'away'|'party')
+
+control_tv(room: str, state: 'on'|'off')
+# room: living_room | bedroom | office
+
+control_fan(room: str, state: 'on'|'off', speed: 'low'|'medium'|'high' = optional)
+# room: living_room | bedroom | kitchen | office
+
+control_speaker(room: str, action: 'play'|'pause'|'stop'|'next'|'previous', media: str = optional)
+# room: living_room | bedroom | kitchen | office | hallway
+
+intent_unclear(reason: 'off_topic'|'incomplete'|'unsupported_device'|'unsupported_feature')
+```
+
+---
+
+## State Format
+
+Every user message must be prefixed with a `[STATE:]` block. 
+
+```text
+[STATE: lights={bedroom:on, kitchen:off, living_room:on}, doors={back:locked, front:unlocked}, thermostat=70F/heat, scene=none, tv={bedroom:off, living_room:on}, speaker={kitchen:stopped}, fan={bedroom:on(low)}, current_user_room=kitchen]
+```
+
+**Field breakdown:**
+
+| Field | Values | Notes |
+|---|---|---|
+| `lights` | `room:on\|off` | Only include connected rooms |
+| `doors` | `door:locked\|unlocked` | Only include connected doors |
+| `thermostat` | `<temp>F/<mode>` | e.g. `72F/heat` |
+| `scene` | scene name or `none` | Active scene or none |
+| `tv` | `{room:on\|off, ...}` | Dictionary of connected TVs |
+| `speaker` | `{room:playing\|paused\|stopped, ...}` | Dictionary of connected speakers |
+| `fan` | `{room:on\|off(speed), ...}` | Dictionary of connected fans |
+| `current_user_room` | room name or empty | Drives pronoun ("this room") resolution |
+
+---
+
+## Usage
+
+### Minimal inference example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "OrdenWills/LFM2.5-350M-home-assistant-sft"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+SYSTEM_PROMPT = """You are a smart home assistant AI. Use tools to control the home.
+
+Output function calls as JSON.
+
+TOOLS:
+  toggle_lights(room, state='on'|'off')
+  toggle_all_lights(state='on'|'off')
+  lock_door(door, state='lock'|'unlock')
+  lock_all_doors(state='lock'|'unlock')
+  set_thermostat(temperature=<int>, mode='heat'|'cool'|'auto')
+  set_scene(scene='movie_night'|'bedtime'|'morning'|'away'|'party')
+  control_tv(room, state='on'|'off')
+  control_fan(room, state='on'|'off'[, speed='low'|'medium'|'high'])
+  control_speaker(room, action='play'|'pause'|'stop'|'next'|'previous'[, media='<str>'])
+  intent_unclear(reason='off_topic'|'incomplete'|'unsupported_device'|'unsupported_feature')
+
+CONNECTED ROOMS (lights): living_room, bedroom, kitchen, bathroom, office, hallway
+CONNECTED DOORS: front, back, garage
+CONNECTED TVs: living_room, bedroom
+CONNECTED SPEAKERS: living_room
+CONNECTED FANS: bedroom
+
+STATE RULES:
+  [STATE:] shows all current device states.
+  State already matches request → plain text reply, NO tool call.
+  Only rooms listed under CONNECTED TVs/SPEAKERS/FANS have those devices.
+  Requesting a device in an unlisted room → intent_unclear(unsupported_device).
+
+TV / SPEAKER / FAN RESOLUTION when user says 'the TV'/'the fan'/'the speaker':
+  1. Exactly one connected → use that room automatically.
+  2. Multiple connected + current_user_room has device → use current_user_room.
+  3. Multiple connected + exactly ONE is in the eligible state for the action
+     (e.g. only one TV is on and user says 'turn off the TV') → infer that room.
+  4. Multiple connected + ambiguous (rule 2 & 3 don't apply) → intent_unclear(incomplete).
+
+LIGHT / DOOR RESOLUTION:
+  current_user_room set + connected → use current_user_room.
+  current_user_room set + NOT connected → intent_unclear(unsupported_device).
+  current_user_room empty → intent_unclear(incomplete).
+
+  [RECENT ACTIONS:] → transaction log, newest entry first. Format:
+    (X mins ago) [call1, call2, ...] -> summary.
+  Each [...] bracket is ONE command the user previously issued.
+  For 'undo'/'reverse'/'back': invert ONLY the most recent transaction
+    (the FIRST [...] block). Older transactions are always ignored.
+  For pronouns ('it'/'them'): refer to the device(s) in the first [...] block.
+  Do NOT use recent actions to infer which room 'the light' or 'the door'
+  refers to when current_user_room is explicitly set — current_user_room wins.
+  For 'all lights' / 'all doors': use toggle_all_lights / lock_all_doors
+  regardless of current_user_room.
+  SYNONYMS: 'open'='unlock'; 'close'/'shut'='lock'; 'skip'='next';
+  'back'='previous' (for speaker track navigation), but can also mean 'undo' for
+  reverting device states based on [RECENT ACTIONS].
+  'continue'/'resume'/'on the music'='play'; 'play <song/artist>' = action='play' + media='<str>'.
+  Relative state clauses ('the light that is on', 'the door that is locked')
+  override current_user_room — check STATE and act on the matching device."""
+
+state = "[STATE: lights={bathroom:off, bedroom:off, hallway:off, kitchen:off, living_room:on, office:off}, doors={back:locked, front:locked, garage:unlocked}, thermostat=70F/heat, scene=none, tv={bedroom:off, living_room:on}, speaker={living_room:stopped}, fan={bedroom:off(medium)}, current_user_room=kitchen]"
+
+messages = [
+    {"role": "system",    "content": SYSTEM_PROMPT},
+    {"role": "user",      "content": f"{state}\nTurn off the TV."},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
+).to(model.device)
+
+with torch.no_grad():
+    output = model.generate(
+        input_ids,
+        max_new_tokens=256,
+        temperature=0.1,        # low temp for deterministic tool calls
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+
+response = tokenizer.decode(
+    output[0][input_ids.shape[-1]:], skip_special_tokens=True
+)
+print(response)
+# Expected behavior: The model will generate a <think> trace noting that only the living_room TV is currently ON, infer the user wants to turn off the living_room TV, conclude with ACTION REQUIRED, and emit the tool call.
+```
+
+### GGUF / Ollama
+
+```bash
+# Pull the recommended q4_k_m quantization
+ollama run hf.co/OrdenWills/LFM2.5-350M-home-assistant-sft:Q4_K_M
+
+# Or use the higher precision q8_0 version
+ollama run hf.co/OrdenWills/LFM2.5-350M-home-assistant-sft:Q8_0
+```
+
+---
+
+## Training Details (Stage 2 Stable)
+
+This release was fine-tuned directly on a 70,000-example state-aware synthetic dataset ("v13 Final Merge"). 
+
+| Parameter | Value |
+|---|---|
+| Base model | LiquidAI/LFM2.5-350M |
+| Dataset Size | 70,000 examples |
+| Categories | 33 distinct instruction schemas |
+| Think Traces | Extensive (Present in majority of complex scenarios) |
+| Hardware | Kaggle T4 (16 GB) |
+
+### Training Categories
+
+| Category | Description | Think Trace? |
+|---|---|---|
+| `already_satisfied` / `state_grounding` | Graceful replies if the device is already in the requested state. Forces reading of state arrays. | **Yes** / No |
+| `action_required` / `relative_clause` | Standard explicit device triggers and relative logic ("turn off the light that is on"). | **Yes** / No |
+| `user_room_lights/doors` | Resolves "the light" / "the door" based on `current_user_room`. | **Yes** |
+| `bulk_plus_local_door` | Complex compound logic mixing global state-aware commands with implicit local commands. | **Yes** |
+| `action_log_*` / `them_plurality` | "Undo", "repeat", "same for bedroom", and resolving plural pronouns using `[RECENT ACTIONS:]`. | **Yes** |
+| `scenes/thermostat` | Standard NLP triggering for scenes and temperature bounds. | No |
+| `rejections/missing` | "Make me coffee", unconnected rooms, and resolving `incomplete` vs `unsupported_device`. | **Yes** / No |
+| `compound_count` | Parallel tool calling with forced sub-action counting before generation. | **Yes** |
+| `status_queries` | "Are the lights on?" / "What is the thermostat set to?" plain text answers. | **Yes** |
+| `tv/speaker/fan commands`| Multi-device disambiguation logic (State inference via `Rule 3` vs implicit fallback). | **Yes**|
+| `local_media_commands` | Parsing local track titles via the `media` parameter for specific song playback. | **Yes** |
+
+**Selective Thinking (`<think>...`):** For complex tasks (e.g., bulk state updates, parsing action logs, determining which TV the user meant based on state arrays, counting compound actions), the model is trained to output a reasoning trace before making the tool call. For direct explicit commands, it skips thinking entirely for speed. All thinking traces now end with explicitly formulated `ACTION REQUIRED.` triggers.
+
+---
+
+## Known Limitations
+
+- **Temperature range is fixed at 60–80°F.** Requests outside this range produce a plain-text explanation, not a tool call. 
+- **No brightness or colour control.** Dimming and colour-change requests correctly trigger `intent_unclear(reason='unsupported_feature')`. This is by design — the connected lights only support on/off.
+- **Local music library only.** The speaker control `media` parameter maps to specific tracks from a bounded internal list of artists and songs. Out-of-domain conversational queries will likely trigger `intent_unclear(reason='off_topic')`.
+- **English only.** All training data is English. Performance in other languages is untested.
+- **State must be accurate.** The model trusts `[STATE:]` completely. If your app sends stale state, the model may incorrectly say a device is already in the requested state or infer the wrong device during disambiguation.
+
+---
+
+## Citation
+
+```bibtex
+@misc{lfm2-home-assistant-2025,
+  author    = {OrdenWills},
+  title     = {LFM2.5-350M Home Assistant: A Purpose-Trained Smart Home Automation Model},
+  year      = {2025},
+  publisher = {HuggingFace},
+  url       = {https://huggingface.co/OrdenWills/LFM2.5-350M-home-assistant-sft}
+}
+```
+
+---
+
+## Acknowledgements
+
+- [LiquidAI](https://www.liquid.ai/) for the incredible and highly capable LFM2.5-350M base model.
+- [Unsloth](https://github.com/unslothai/unsloth) for the fine-tuning framework.
+```

chat_template.jinja

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+{{- bos_token -}}
+{%- set keep_past_thinking = keep_past_thinking | default(false) -%}
+{%- set ns = namespace(system_prompt="") -%}
+{%- if messages[0]["role"] == "system" -%}
+    {%- set sys_content = messages[0]["content"] -%}
+    {%- if sys_content is not string -%}
+        {%- for item in sys_content -%}
+            {%- if item["type"] == "text" -%}
+                {%- set ns.system_prompt = ns.system_prompt + item["text"] -%}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {%- set ns.system_prompt = sys_content -%}
+    {%- endif -%}
+    {%- set messages = messages[1:] -%}
+{%- endif -%}
+{%- if tools -%}
+    {%- set ns.system_prompt = ns.system_prompt + ("\n" if ns.system_prompt else "") + "List of tools: [" -%}
+    {%- for tool in tools -%}
+        {%- if tool is not string -%}
+            {%- set tool = tool | tojson -%}
+        {%- endif -%}
+        {%- set ns.system_prompt = ns.system_prompt + tool -%}
+        {%- if not loop.last -%}
+            {%- set ns.system_prompt = ns.system_prompt + ", " -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {%- set ns.system_prompt = ns.system_prompt + "]" -%}
+{%- endif -%}
+{%- if ns.system_prompt -%}
+    {{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
+{%- endif -%}
+{%- set ns.last_assistant_index = -1 -%}
+{%- for message in messages -%}
+    {%- if message["role"] == "assistant" -%}
+        {%- set ns.last_assistant_index = loop.index0 -%}
+    {%- endif -%}
+{%- endfor -%}
+{%- for message in messages -%}
+    {{- "<|im_start|>" + message["role"] + "\n" -}}
+    {%- set content = message["content"] -%}
+    {%- if content is not string -%}
+        {%- set ns.content = "" -%}
+        {%- for item in content -%}
+            {%- if item["type"] == "image" -%}
+                {%- set ns.content = ns.content + "<image>" -%}
+            {%- elif item["type"] == "text" -%}
+                {%- set ns.content = ns.content + item["text"] -%}
+            {%- else -%}
+                {%- set ns.content = ns.content + item | tojson -%}
+            {%- endif -%}
+        {%- endfor -%}
+        {%- set content = ns.content -%}
+    {%- endif -%}
+    {%- if message["role"] == "assistant" and not keep_past_thinking and loop.index0 != ns.last_assistant_index -%}
+        {%- if "</think>" in content -%}
+            {%- set content = content.split("</think>")[-1] | trim -%}
+        {%- endif -%}
+    {%- endif -%}
+    {{- content + "<|im_end|>\n" -}}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{- "<|im_start|>assistant\n" -}}
+{%- endif -%}

config.json

@@ -0,0 +1,62 @@
+{
+  "architectures": [
+    "Lfm2ForCausalLM"
+  ],
+  "block_auto_adjust_ff_dim": true,
+  "block_dim": 1024,
+  "block_ffn_dim_multiplier": 1.0,
+  "block_mlp_init_scale": 1.0,
+  "block_multiple_of": 256,
+  "block_norm_eps": 1e-05,
+  "block_out_init_scale": 1.0,
+  "block_use_swiglu": true,
+  "block_use_xavier_init": true,
+  "bos_token_id": 1,
+  "conv_L_cache": 3,
+  "conv_bias": false,
+  "conv_dim": 1024,
+  "conv_use_xavier_init": true,
+  "dtype": "float16",
+  "eos_token_id": 7,
+  "full_attn_idxs": null,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 6656,
+  "layer_types": [
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "full_attention",
+    "conv",
+    "full_attention",
+    "conv"
+  ],
+  "max_position_embeddings": 128000,
+  "model_name": "LiquidAI/LFM2.5-350M",
+  "model_type": "lfm2",
+  "norm_eps": 1e-05,
+  "num_attention_heads": 16,
+  "num_heads": 16,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pad_token_id": 7,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.5.0",
+  "unsloth_version": "2026.5.2",
+  "use_cache": false,
+  "use_pos_enc": true,
+  "vocab_size": 64402
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": [
+    7
+  ],
+  "max_length": 128000,
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