Update README.md

README.md

@@ -1,13 +1,18 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- gemma
+- text-generation
+- transformers
+- custom-trained
+- instruction-tuned
 ---
 
-# Model Card for Model ID
+# Model Card for JMK001/gemma-3-270m-oig-transformers-merged
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-
+Un modèle Gemma-3-270M optimisé et fusionné, spécialement adapté pour le traitement de texte et la génération de contenu.
 
 ## Model Details
 
@@ -15,23 +20,23 @@ tags: []
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+Ce modèle est une version optimisée de Gemma-3-270M qui a été fusionnée et fine-tunée sur des données d'instruction OIG (Open Instruction Generalist) pour améliorer ses capacités de compréhension et de génération de texte. Le modèle offre un bon équilibre entre performance et efficacité computationnelle.
 
-- **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]
+- **Developed by:** JMK
+- **Funded by [optional]:** OVerAI
+- **Shared by [optional]:** JMK
+- **Model type:** Transformer-based Language Model
+- **Language(s) (NLP):** Multilingue (dominante anglaise)
+- **License:** Custom (consulter la licence originale Gemma)
+- **Finetuned from model [optional]:** Gemma-3-270M
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [Lien vers le dépôt GitHub si disponible]
+- **Paper [optional]:** [Gemma: Open Models Based on Gemini Research and Technology]
+- **Demo [optional]:** [Lien vers démo Hugging Face Spaces si disponible]
 
 ## Uses
 
@@ -41,159 +46,67 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+- Génération de texte
+- Réponse à des questions
+- Rédaction de contenu
+- Assistance conversationnelle
+- Résumé de texte
 
 ### 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]
+- Chatbots spécialisés
+- Systèmes de support client
+- Outils d'aide à la rédaction
+- Applications éducatives
+- Analyse de sentiment
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-[More Information Needed]
+- Génération de contenu illégal ou nuisible
+- Conseils médicaux ou juridiques
+- Prise de décisions critiques
+- Désinformation
+- Contenu à caractère sexuel explicite
 
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+Comme tous les modèles de langue, ce modèle peut présenter des biais présents dans les données d'entraînement. Les limitations incluent :
+
+- Connaissance limitée aux événements postérieurs à la date d'entraînement
+- Possibilité de générer des informations inexactes
+- Sensibilité aux formulations des prompts
+- Biais culturels et linguistiques
 
 ### 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.
+Les utilisateurs doivent :
+- Vérifier les informations importantes générées par le modèle
+- Être conscients des limitations potentielles
+- Utiliser le modèle de manière éthique et responsable
+- Mettre en place des filtres de contenu appropriés
 
 ## 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]
+Utilisez le code suivant pour commencer avec le modèle :
 
-[More Information Needed]
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
 
-## Model Card Contact
+model_name = "JMK001/gemma-3-270m-oig-transformers-merged"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-[More Information Needed]
+# Génération de texte
+input_text = "Explain the concept of machine learning:"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=200)
+print(tokenizer.decode(outputs[0]))