update model card

README.md

@@ -1,3 +1,99 @@
 ---
 license: llama2
+language:
+- it
+tags:
+- text-generation-inference
 ---
+# Model Card for LLaMAntino-2-chat-13b-UltraChat-ITA
+
+## Model description
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+**LLaMAntino-2-chat-13b-UltraChat** is a *Large Language Model (LLM)* that is an instruction-tuned version of **LLaMAntino-2-chat-13b** (an italian-adapted **LLaMA 2 chat**). 
+This model aims to provide Italian NLP researchers with an improved model for italian dialogue use cases.
+
+The model was trained using *QLora* and using as training data [UltraChat](https://github.com/thunlp/ultrachat) translated to the italian language using [Argos Translate](https://pypi.org/project/argostranslate/1.4.0/). 
+If you are interested in more details regarding the training procedure, you can find the code we used at the following link:
+- **Repository:** https://github.com/swapUniba/LLaMAntino
+
+**NOTICE**: the code has not been released yet, we apologize for the delay, it will be available asap!
+
+- **Developed by:** Pierpaolo Basile, Elio Musacchio, Marco Polignano, Lucia Siciliani, Giuseppe Fiameni, Giovanni Semeraro
+- **Funded by:** PNRR project FAIR - Future AI Research
+- **Compute infrastructure:** [Leonardo](https://www.hpc.cineca.it/systems/hardware/leonardo/) supercomputer
+- **Model type:** LLaMA-2-chat
+- **Language(s) (NLP):** Italian
+- **License:** Llama 2 Community License 
+- **Finetuned from model:** [swap-uniba/LLaMAntino-2-chat-13b-hf-ITA](https://huggingface.co/swap-uniba/LLaMAntino-2-chat-13b-hf-ITA)
+
+## Prompt Format
+
+This prompt format based on the [LLaMA 2 prompt template](https://gpus.llm-utils.org/llama-2-prompt-template/) adapted to the italian language was used:
+
+```python
+"<s>[INST] <<SYS>>\n" \
+"Sei un assistente disponibile, rispettoso e onesto. " \
+"Rispondi sempre nel modo piu' utile possibile, pur essendo sicuro. " \
+"Le risposte non devono includere contenuti dannosi, non etici, razzisti, sessisti, tossici, pericolosi o illegali. " \
+"Assicurati che le tue risposte siano socialmente imparziali e positive. " \
+"Se una domanda non ha senso o non e' coerente con i fatti, spiegane il motivo invece di rispondere in modo non corretto. " \
+"Se non conosci la risposta a una domanda, non condividere informazioni false.\n" \
+"<</SYS>>\n\n" \
+f"{user_msg_1} [/INST] {model_answer_1} </s><s>[INST] {user_msg_2} [/INST] {model_answer_2} </s> ... <s>[INST] {user_msg_N} [/INST] {model_answer_N} </s> "
+```
+
+We recommend using the same prompt in inference to obtain the best results!
+
+## How to Get Started with the Model
+
+Below you can find an example of model usage:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "swap-uniba/LLaMAntino-2-chat-13b-hf-UltraChat-ITA"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+user_msg = "Ciao! Come stai?"
+
+prompt = "<s>[INST] <<SYS>>\n" \
+         "Sei un assistente disponibile, rispettoso e onesto. " \
+         "Rispondi sempre nel modo piu' utile possibile, pur essendo sicuro. " \
+         "Le risposte non devono includere contenuti dannosi, non etici, razzisti, sessisti, tossici, pericolosi o illegali. " \
+         "Assicurati che le tue risposte siano socialmente imparziali e positive. " \
+         "Se una domanda non ha senso o non e' coerente con i fatti, spiegane il motivo invece di rispondere in modo non corretto. " \
+         "Se non conosci la risposta a una domanda, non condividere informazioni false.\n" \
+         "<</SYS>>\n\n" \
+         f"{user_msg} [/INST] "
+
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+outputs = model.generate(input_ids=input_ids, max_length=1024)
+
+print(tokenizer.batch_decode(outputs.detach().cpu().numpy()[:, input_ids.shape[1]:], skip_special_tokens=True)[0])
+```
+
+If you are facing issues when loading the model, you can try to load it quantized:
+
+```python
+model = AutoModelForCausalLM.from_pretrained(model_id, load_in_8bit=True)
+```
+
+*Note*: The model loading strategy above requires the [*bitsandbytes*](https://pypi.org/project/bitsandbytes/) and [*accelerate*](https://pypi.org/project/accelerate/) libraries
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+*Coming soon*!
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+If you use this model in your research, please cite the following:
+
+*Coming soon*!