alinia
/

salamandra-7b-aligned-EADOP

@@ -1,199 +1,97 @@
 ---
 library_name: transformers
-tags: []
 ---
-# 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. -->
-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:** [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]

 ---
 library_name: transformers
+pipeline_tag: text-generation
+language:
+- ca
+- es
+license: apache-2.0
+base_model:
+- BSC-LT/salamandra-7b-instruct
+tags:
+- legal
 ---
+# Salamandra 7B aligned EADOP Model Card
+Salamandra 7B aligned EADOP is a full finetuning version of
+[BSC Language Technologies Unit](https://huggingface.co/BSC-LT)'s
+[Salamndra Instruct 7B](https://huggingface.co/BSC-LT/salamandra-7b-instruct)
+model by the  at the Barcelona Supercomputing Center focused on improving
+the handling of out-of-domain Questions in a RAG instruction-following setting.
+The model has been finetuned on a dataset dataset consisting of 2,000+ human annotated in-
+and out-of-domain user messages and assitant responses in the context of a chatbot that can
+provide helpful information about the current Catalan legislation.
+The dataset [Link Pending] was collected in collaboration with the
+[Entitat Autònoma del Diari Oficial i de Publicacions (EADOP)](https://dogc.gencat.cat/ca/sobre-el-dogc/eadop/)
+and it consists of user messages and assistant responses in Catalan and Spanish.
+> [!WARNING]
+> **DISCLAIMER:** This model is a proof-of-concept designed to demonstrate the effects of
+finetuning an Instruction model with a small dataset of out-of-domain questions in the model's
+capability to politely and informatively refuse to answer questions that are out-of-domain.
+> As a proof-of-concept, the model is still prone to generate harmful or inappropriate content.
+---
 ## Model Details
+Please refer to the [Salamndra Instruct 7B model details](https://huggingface.co/BSC-LT/salamandra-7b-instruct#model-details)
+for the specific details about the model architecture and pretraining.
+## Intended Use
+This model was developed as a proof-of-concept to demonstrate the effects of finetuning
+an Instruction model with a small dataset of in- and out-of-domain questions in the model's
+capability to politely and informatively refuse to answer questions that are out-of-domain in
+the context of a domain-specific RAG-based chatbot.
+## How to use
+This model uses the ChatML, the same instruction-following conversation format as the base model.
+```python
+from datetime import datetime
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+model_id = "BSC-LT/salamandra-7b-instruct"
+text = "At what temperature does water boil?"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+    torch_dtype=torch.bfloat16
+  )
+message = [ { "role": "user", "content": text } ]
+prompt = tokenizer.apply_chat_template(
+    message,
+    tokenize=False,
+    add_generation_prompt=True
+)
+inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
+outputs = model.generate(input_ids=inputs.to(model.device), max_new_tokens=200)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+Using this template, each turn is preceded by a `<|im_start|>` delimiter and the role of the entity
+(either `user`, for content supplied by the user, or `assistant` for LLM responses), and finished with the `<|im_end|>` token.
+---
+## Finetuning Data
+Please refer to [Link Pending]
+### Author
+This model has been finetuned by [Alinia AI](https://alinia.ai/).
+### Contact
+For further information, please send an email to [[email protected]](mailto:[email protected]).
+### Acknowledgements
+This project is part of a partnership with the Language Technologies Unit at the [Barcelona Supercomputing Center](https://www.bsc.es/).
+The data collection process was supported by the [Entitat Autònoma del Diari Oficial i de Publicacions (EADOP)](https://dogc.gencat.cat/ca/sobre-el-dogc/eadop/).