Update README.md

README.md

@@ -1,6 +1,9 @@
 ---
 library_name: transformers
-tags: []
+license: cc-by-nc-sa-4.0
+language:
+- fr
+base_model: OpenLLM-France/Claire-7B-0.1
 ---
 
 # Model Card for Model ID
@@ -13,65 +16,35 @@ tags: []
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+This is the instruction-finetuned model based on ([OpenLLM-France/Claire-7B-EN-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-EN-0.1)), using the [Vigogne dataset](https://github.com/bofenghuang/vigogne).
+Note: This is not a chat model. The finetuning was done on instruction-following data, and the model should be used with the template as shown in "How to Get Started with the Model".
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+- **Developed by:** OpenLLM-France
+- **Language(s) (NLP):** French
+- **License:** CC-BY-NC-SA 4.0
+- **Finetuned from model: [OpenLLM-France/Claire-7B-EN-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-EN-0.1)
 
-- **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
 
-### Model Sources [optional]
+- **Repository:** [OpenLLM-France/Claire-7B-EN-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-EN-0.1)
+- **Paper:** [Claire: Large Language Models for Spontaneous French Dialogue](https://aclanthology.org/2024.jeptalnrecital-taln.36/)
 
-<!-- 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]
+This instruction-finetuned model is designed for tasks requiring detailed responses to user instructions. 
+It can be used for generating natural language responses, content creation, answering queries, and other instruction-based tasks.
 
-### 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.
+This model may reflect biases present in the data it was trained on, potentially leading to unintended or biased responses. 
 
 ## How to Get Started with the Model
 
 Use the code below to get started with the model.
 
-```
+```python
 import torch
 from peft import PeftModel    
 from transformers import AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
@@ -112,96 +85,37 @@ print(decoded_output[0])
 
 ### 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]
+The model was finetuned on the [Vigogne dataset](https://github.com/bofenghuang/vigogne), which is a translation of the [Alpaca dataset](https://huggingface.co/datasets/tatsu-lab/alpaca).
 
 ### 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]
-
+The model was finetuned using LoRA.
 
 #### 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]
+```
+lora_rank: 8
+lora_alpha: 16
+lora_dropout: 0.05
+lora_bias: none
+learning_rate: 0.0001
+lora_target_modules: ['query_key_value', 'dense_h_to_4h', 'dense_4h_to_h', 'dense'] │
+lora_task_type: CAUSAL_LM
+num_train_epochs: 1
+```
 
 ## 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
+#### Summary
 
-[More Information Needed]
 
 ## Citation [optional]