Update README.md

README.md

@@ -1,6 +1,19 @@
 ---
-library_name: transformers
-tags: []
+license: apache-2.0
+language:
+- it
+pipeline_tag: text-generation
+tags:
+- text-generation-inference
+- transformers
+- mistral
+- trl
+- sft
+datasets:
+- mchl-labs/stambecco_data_it
+widget:
+- text: "Di seguito è riportata un'istruzione che descrive un'attività, abbinata ad un input che fornisce ulteriore informazione. Scrivi una risposta che soddisfi adeguatamente la richiesta. \n### Istruzione:\nSuggerisci un'attività serale romantica\n\n### Input:\n\n### Risposta:"
+  example_title: Example 1
 ---
 
 # Model Card for Model ID
@@ -17,13 +30,10 @@ tags: []
 
 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]
+- **Developed by:** Walid Iguider
+- **Model type:** Minerva
+- **License:** cc-by-nc-sa-4.0
+- **Finetuned from model :** sapienzanlp/Minerva-3B-base-v1.0
 
 ### Model Sources [optional]
 
@@ -36,7 +46,49 @@ This is the model card of a 🤗 transformers model that has been pushed on 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. -->
-
+### Sample Code
+
+```python
+  from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+  import torch
+  torch.random.manual_seed(0)
+  # Run text generation pipeline with our next model
+  prompt = """Di seguito è riportata un'istruzione che descrive un'attività, abbinata ad un input che fornisce
+  ulteriore informazione. Scrivi una risposta che soddisfi adeguatamente la richiesta.
+  
+  ### Istruzione:
+  Suggerisci un'attività serale romantica
+
+  ### Input:
+  
+  
+  ### Risposta:"""
+  
+  model_id = "walid-iguider/Minerva-3B-Instruct-v1.0"
+  tokenizer = AutoTokenizer.from_pretrained(model_id)
+  model = AutoModelForCausalLM.from_pretrained(
+      model_id, 
+      device_map="cuda", 
+      torch_dtype="auto", 
+      trust_remote_code=True, 
+  )
+  
+  generation_args = {
+      "max_new_tokens": 500,
+      "return_full_text": False,
+      "temperature": 0.0,
+      "do_sample": False,
+  }
+  
+  pipe = pipeline(
+      "text-generation",
+      model=model,
+      tokenizer=tokenizer,
+  )
+  
+  output = pipe(prompt, **generation_args)
+  print(output[0]['generated_text'])
+```
 ### Direct Use
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->