Ficha del modelo actualizada

README.md

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+---
+base_model: HuggingFaceTB/SmolLM2-360M-Instruct
+library_name: peft
+---
+
+# Model Card for SmolLM2-360M-Instruct LoRA (finetuned)
+ENGLISH:
+This model is a fine-tuned version of HuggingFaceTB/SmolLM2-360M-Instruct using LoRA. It was trained on 550 example entries, focused on generative language tasks in an instructive style. The resulting model is designed to remain highly efficient on resource-limited devices, with a focus on character simulation and conversational tasks.
+
+ESPAÑOL:
+Este modelo es una versión ajustada de `HuggingFaceTB/SmolLM2-360M-Instruct` utilizando fine-tuning LoRA. Ha sido entrenado con 550 entradas de ejemplo, enfocadas en tareas de lenguaje generativo con estilo instructivo. El modelo resultante busca mantener una alta eficiencia en dispositivos con recursos limitados, con enfoque en tareas conversacionales de simulación de personajes.
+
+## Model Details
+
+### Model Description
+
+- **Developed by:** ElMagoRubio
+- **Model type:** Causal Language Model
+- **Language(s):** Español (principal)
+- **License:** ENGLISH: This model is a LoRA fine-tuned version of `HuggingFaceTB/SmolLM2-360M-Instruct` and is distributed under the same Apache 2.0 license. ESPAÑOL: 
+- **Finetuned from model:** HuggingFaceTB/SmolLM2-360M-Instruct
+
+### Model Sources
+
+- **Repository:** ElMagoRubio
+
+## Uses
+
+### Direct Use
+ENGLISH:
+Intended for text generation tasks in Spanish, especially in environments where lightweight and efficient models are required. This model is currently under training.
+
+ESPAÑOL:
+Pensado para tareas de generación de texto en español, especialmente en entornos donde se requieren modelos ligeros y eficientes. Este modelo está en proceso de entrenamiento.
+
+### Downstream Use
+ENGLISH:
+This model is integrated into the interactive role-playing game Words & Swords, which is still in development. It is part of a Final Project for the Universidad de Granada (UGR)
+
+ESPAÑOL:
+Este modelo se integra en el juego de rol interactivo "Word & Swords", aún en desarrollo. Forma parte de un TFG para la Universidad de Granada (UGR)
+
+### Out-of-Scope Use
+ENGLISH:
+Not designed for complex multilingual tasks, numerical data processing, or deep logical reasoning.
+
+ESPAÑOL:
+No está diseñado para tareas multilingües complejas, procesamiento de datos numéricos o razonamiento lógico profundo.
+
+## Bias, Risks, and Limitations
+ENGLISH:
+The model may reflect biases present in the training data. It should not be used in critical contexts without human review.
+
+ESPAÑOL:
+El modelo puede reflejar sesgos presentes en los datos de entrenamiento. No debe utilizarse en contextos críticos sin revisión humana.
+
+### Recommendations
+ENGLISH:
+Evaluate and audit sensitive outputs. Do not use in medical, legal, or financial contexts without specialized validation.
+
+ESPAÑOL:
+Evaluar y auditar salidas sensibles. No usar en contextos médicos, legales o financieros sin validación especializada.
+
+## How to Get Started with the Model
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "ElMagoRubio/SmolLM2-360M-Instruct-lora"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)

adapter_config.json

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+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "C:\\Users\\34644\\Desktop\\Facultad\\TFG\\WordsNSwords_copia\\WordsAndSwords\\language_models\\model\\HuggingFaceTB_SmolLM2-360M-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "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": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

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checkpoint-5000/README.md

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+---
+base_model: C:\Users\34644\Desktop\Facultad\TFG\WordsNSwords_copia\WordsAndSwords\language_models\model\HuggingFaceTB_SmolLM2-360M-Instruct
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.15.2

checkpoint-5000/adapter_config.json

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+  "use_rslora": false
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