Update README.md

README.md

@@ -31,42 +31,92 @@ This repository contains the model merged with the LoRA adapters obtained in the
 ## 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. -->
+The model can be used as is to respond to simple instructions in Italian or can be further fine-tuned to perform specific tasks.
 
-### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+## Bias, Risks, and Limitations
 
-### Downstream Use [optional]
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+As any other LLM it is possible that the model generates content which does not correspond to the reality as well as wrong, biased, offensive and inappropriate answers.
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
-[More Information Needed]
+## How to Get Started with the Model
+ **Prompt template:**
 
-### Out-of-Scope Use
+ ``` python
+"Di seguito è riportata un'istruzione che descrive un compito, abbinata a un input che fornisce un ulteriore contesto. Scrivete una risposta che completi in modo appropriato la richiesta.
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+### Istruzione:
+{instruction}
 
-[More Information Needed]
+### Input:
+{input}
 
-## Bias, Risks, and Limitations
+### Risposta:"
+```
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+ **Usage:**
+Use the code below to get started with the model.
+ ``` python
+import os
+import torch
+import sys
+from transformers import LlamaTokenizer, LlamaForCausalLM
 
-[More Information Needed]
+if torch.cuda.is_available():
+    device = "cuda"
+else:
+    device = "cpu"
 
-### Recommendations
+def generate_prompt(instruction, input=None):
+    if input:
+        return f"""Di seguito è riportata un'istruzione che descrive un compito, abbinata a un input che fornisce un ulteriore contesto. Scrivete una risposta che completi in modo appropriato la richiesta.
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+### Istruzione:
+{instruction}
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+### Input:
+{input}
 
-## How to Get Started with the Model
+### Risposta:"""
+    else:
+        return f"""Di seguito è riportata un'istruzione che descrive un compito. Scrivete una risposta che completi in modo appropriato la richiesta..
 
-Use the code below to get started with the model.
+### Istruzione:
+{instruction}
+
+### Risposta:"""
 
-[More Information Needed]
+model_name = "raicrits/OpenLLama13b_Loquace_ITA"
+
+model = LlamaForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+tokenizer = LlamaTokenizer.from_pretrained(model_name)
+
+instruction = "qual'è la relazione tra i seguenti oggetti"
+input = "sedia, tavolo, divano"
+prompt = generate_prompt("instruction", input)
+inputs = tokenizer(prompt, return_tensors="pt")
+input_ids = inputs["input_ids"].to(device)
+
+generation_output = model.generate(
+    input_ids=input_ids,
+    max_new_tokens=256,
+)
+
+
+output = tokenizer.decode(generation_output[0])
+output = output.split("### Risposta:")[1].strip().replace("</s>","")
+print(output)
+```
+``` python
+"Sedia, tavolo e divano sono tutti oggetti che possono essere utilizzati per creare un'atmosfera rilassante in una stanza."
+```
 
 ## Training Details
 
@@ -108,8 +158,6 @@ The fine-tuning procedure was done using [LoRA](https://arxiv.org/pdf/2106.09685
   
 
 
-[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 -->
@@ -121,47 +169,8 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 - **Cloud Provider:** Private Infrastructure
 - **Carbon Emitted:** 7.34 kg eq. CO2
 
-## 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]
+## Model Card Authors
 
 Stefano Scotta (stefano.scotta@rai.it)