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Model: Smith-3/simon-fcyt-umss
Source: Original Platform

.gitattributes

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README.md

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+---
+license: other
+tags:
+  - gguf
+  - llama.cpp
+  - unsloth
+  - lfm2
+  - structured-output
+  - notification-ai
+  - spanish
+  - education
+datasets:
+  - Smith-3/simon-fcyt-umss
+language:
+  - es
+  - en
+base_model: LiquidAI/LFM2-350M
+pipeline_tag: text-generation
+---
+
+# simon-fcyt-umss (GGUF) 🎓✨  
+Modelo de IA ajustado para la **Facultad de Ciencias y Tecnología – Universidad Mayor de San Simón (UMSS)**,  
+diseñado para la aplicación **TecnoTime**, la cual ayuda a estudiantes a mantenerse organizados, motivados y conectados con sus actividades académicas.
+
+Este modelo es un **fine-tuning** de `LiquidAI/LFM2-350M` orientado a producir respuestas **consistentes, validadas y parseables**, siguiendo la clase `SimonResponse` del sistema Android.
+
+La conversión a **GGUF** se realizó usando **Unsloth**, optimizando su uso en:
+- `llama.cpp`
+- `text-generation-webui`
+- dispositivos con recursos limitados (laptops modestos, labs universitarios, teléfonos con inferencia local)
+
+---
+
+## 🎯 Propósito Académico
+Este modelo está orientado a:
+- Recordatorios de clases y horarios
+- Mensajes motivacionales para mejorar continuidad académica
+- Check-ins cortos para acompañamiento del progreso diario
+- Estímulo positivo en momentos clave del semestre
+
+Está pensado para reforzar:
+> Hábitos, constancia, asistencia, estado de ánimo y autocuidado académico.
+
+---
+
+## 🧱 Formato Estructurado de Respuesta (JSON Obligatorio)
+
+La salida del modelo **no es texto libre**.  
+Siempre debe generar **un único objeto JSON** con los campos requeridos:
+
+{
+  "why": "...",
+  "opening_tag": "...",
+  "icon_tag": "...",
+  // Campos adicionales según tipo de notificación
+}
+
+### Campos según tipo de template:
+
+Tipo de Notificación | Requiere | Opcional | Sin
+---------------------|----------|----------|-----
+MOTIVATIONAL_CHECK_IN | question, choices (2) | — | —
+CLASS_REMINDER | question, choices (2) | — | —
+CHECK_IN_CLOSURE | message o reminder_copy | — | choices
+REMINDER_CLOSURE | reminder_copy | — | choices
+
+---
+
+## ✅ Ejemplos Reales Usados en TecnoTime
+
+### Recordatorio de Clase
+{
+  "why": "Para que no pierdas tu ritmo académico",
+  "opening_tag": "¡Atención, estudiante FCyT!",
+  "question": "¿Listo para tu clase de hoy?",
+  "icon_tag": "info",
+  "choices": [
+    {"id": "yes", "label": "Llego en un momento"},
+    {"id": "no", "label": "Estoy terminando algo"}
+  ]
+}
+
+### Check-in Motivacional
+{
+  "why": "Para reforzar tu constancia",
+  "opening_tag": "¡Vamos con toda, ingeniería!",
+  "question": "¿Cómo te sientes con lo que has avanzado hoy?",
+  "icon_tag": "focus",
+  "choices": [
+    {"id": "yes", "label": "Bien, sigo avanzando"},
+    {"id": "no", "label": "Hoy fue complicado"}
+  ]
+}
+
+---
+
+## 📦 Archivos GGUF Disponibles
+
+Archivo | Uso recomendado
+--------|----------------
+LFM2-350M.Q5_K_M.gguf | Mejor equilibrio calidad / rendimiento
+LFM2-350M.Q8_0.gguf | Máxima calidad (requiere más RAM)
+LFM2-350M.Q4_K_M.gguf | Equipos de bajos recursos / labs
+
+---
+
+## 🚀 Uso con `llama.cpp`
+
+llama-cli -m LFM2-350M.Q5_K_M.gguf -p "GENERAR: CLASS_REMINDER para clase de Física"
+
+---
+
+## 🐍 Uso con `transformers`
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("tuUsuario/simon-fcyt-umss")
+model = AutoModelForCausalLM.from_pretrained("tuUsuario/simon-fcyt-umss")
+
+prompt = "GENERAR: MOTIVATIONAL_CHECK_IN"
+inp = tokenizer(prompt, return_tensors="pt")
+out = model.generate(**inp, max_new_tokens=160)
+print(tokenizer.decode(out[0], skip_special_tokens=True))
+
+---
+
+## ⚖️ Licencia
+Este modelo deriva de `LiquidAI/LFM2-350M`, bajo:
+
+LFM Open License v1.0
+https://huggingface.co/LiquidAI/LFM2-350M/blob/main/LICENSE
+
+---
+
+## 📌 Estado
+✅ Listo para uso en TecnoTime  
+⏳ Próxima etapa: Publicación en Play Store  
+🔗 Enlace será añadido próximamente.

chat_template.jinja

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+{{- bos_token -}}
+{%- set system_prompt = "" -%}
+{%- set ns = namespace(system_prompt="") -%}
+{%- if messages[0]["role"] == "system" -%}
+	{%- set ns.system_prompt = messages[0]["content"] -%}
+	{%- set messages = messages[1:] -%}
+{%- endif -%}
+{%- if tools -%}
+	{%- set ns.system_prompt = ns.system_prompt + ("\n" if ns.system_prompt else "") + "List of tools: <|tool_list_start|>[" -%}
+	{%- 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 + "]<|tool_list_end|>" -%}
+{%- endif -%}
+{%- if ns.system_prompt -%}
+	{{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
+{%- endif -%}
+{%- for message in messages -%}
+	{{- "<|im_start|>" + message["role"] + "\n" -}}
+	{%- set content = message["content"] -%}
+	{%- if content is not string -%}
+		{%- set content = content | tojson -%}
+	{%- endif -%}
+	{%- if message["role"] == "tool" -%}
+		{%- set content = "<|tool_response_start|>" + content + "<|tool_response_end|>" -%}
+	{%- endif -%}
+	{{- content + "<|im_end|>\n" -}}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+	{{- "<|im_start|>assistant\n" -}}
+{%- endif -%}

config.json

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+{
+  "architectures": [
+    "Lfm2ForCausalLM"
+  ],
+  "block_auto_adjust_ff_dim": true,
+  "block_dim": 1024,
+  "block_ff_dim": 6656,
+  "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_dim_out": 1024,
+  "conv_use_xavier_init": true,
+  "eos_token_id": 7,
+  "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_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": 0,
+  "rope_theta": 1000000.0,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.54.0",
+  "use_cache": true,
+  "use_pos_enc": true,
+  "vocab_size": 65536
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 7,
+  "pad_token_id": 0,
+  "transformers_version": "4.54.0"
+}

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|pad|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}