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Model: swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
Source: Original Platform

LICENSE.txt

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README.md

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+---
+language:
+- en
+- it
+license: llama3
+library_name: transformers
+tags:
+- facebook
+- meta
+- pythorch
+- llama
+- llama-3
+- llamantino
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- gsarti/clean_mc4_it
+- Chat-Error/wizard_alpaca_dolly_orca
+- mlabonne/orpo-dpo-mix-40k
+metrics:
+- accuracy
+model_creator: Marco Polignano - SWAP Research Group
+pipeline_tag: text-generation
+model-index:
+- name: LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 74.57
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 92.75
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 66.85
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 75.93
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 82.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 58.61
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
+      name: Open LLM Leaderboard
+---
+<img src="https://cdn-uploads.huggingface.co/production/uploads/5df8bb21da6d0311fd3d540f/xL6Ax1I34qfC4VPKEFA6Z.png" alt="llamantino3_anita" border="0" width="800px">
+
+<hr>
+
+📣 New MODEL FAMILY❗ [https://huggingface.co/m-polignano/ANITA-NEXT-24B-Magistral-2506-VISION-ITA](https://huggingface.co/m-polignano/ANITA-NEXT-24B-Magistral-2506-VISION-ITA)
+
+<hr>
+<!--<img src="https://i.ibb.co/6mHSRm3/llamantino53.jpg" width="200"/>-->
+<h3><i>"Built with <b>Meta Llama 3</b>".</i></i></h3>
+<p style="text-align:justify;"><b>LLaMAntino-3-ANITA-8B-Inst-DPO-ITA</b> is a model of the <a href="https://huggingface.co/swap-uniba"><b>LLaMAntino</b></a> - <i>Large Language Models family</i>.
+The model is an instruction-tuned version of <a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct"><b>Meta-Llama-3-8b-instruct</b></a> (a fine-tuned <b>LLaMA 3 model</b>).
+This model version aims to be the a <b>Multilingual Model</b> 🏁  (EN 🇺🇸 + ITA🇮🇹) to further fine-tuning on Specific Tasks in Italian.</p>
+
+
+The 🌟**ANITA project**🌟 *(**A**dvanced **N**atural-based interaction for the **ITA**lian language)*
+wants to provide Italian NLP researchers with an improved model for the Italian Language 🇮🇹 use cases.<br>
+
+<hr>
+
+**Live DEMO:** [https://chat.llamantino.it/](https://chat.llamantino.it/)<br>
+*It works only with Italian connection.*
+
+<hr>
+
+## Model Details
+*Last Update: 10/05/2024*<br>
+
+<a href="https://github.com/marcopoli/LLaMAntino-3-ANITA"><img src="https://github.githubassets.com/assets/GitHub-Logo-ee398b662d42.png" width="150"> https://github.com/marcopoli/LLaMAntino-3-ANITA</a><br>
+
+| Model | HF   | GGUF   | EXL2   |
+|-------|-------|-------|-------|
+| *swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA* | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA) | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA_GGUF) | [Link](https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA_EXL2) |
+
+<hr>
+
+## Specifications
+
+- **Model developers**: <br><a href="https://marcopoli.github.io/">Ph.D. Marco Polignano</a> - University of Bari Aldo Moro, Italy <br> <a href="https://huggingface.co/swap-uniba">SWAP Research Group</a> <br>
+- **Variations**: The model release has been **supervised fine-tuning (SFT)** using **QLoRA** 4bit, on instruction-based datasets. **DPO** approach over the *mlabonne/orpo-dpo-mix-40k* dataset is used to align with human preferences for helpfulness and safety.
+- **Input**: Models input text only.
+- **Language**: Multilingual 🏁 + Italian 🇮🇹
+- **Output**: Models generate text and code only.
+- **Model Architecture**: *Llama 3 architecture*.
+- **Context length**: 8K, 8192.
+- **Library Used**: [Unsloth](https://unsloth.ai/)
+<hr>
+
+## Playground
+
+To use the model directly, there are many ways to get started, choose one of the following ways to experience it.
+
+### Prompt Template
+```
+<|start_header_id|>system<|end_header_id|>
+
+{ SYS Prompt }<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+{ USER Prompt }<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+{ ASSIST Prompt }<|eot_id|>
+````
+
+### Transformers
+
+For direct use with `transformers`, you can easily get started with the following steps.
+
+- Firstly, you need to install transformers via the command below with `pip`.
+
+  ```bash
+  pip install -U transformers trl peft accelerate bitsandbytes
+  ```
+
+- Right now, you can start using the model directly.
+
+  ```python
+  import torch
+  from transformers import (
+      AutoModelForCausalLM,
+      AutoTokenizer,
+  )
+  
+  base_model = "swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA"
+  model = AutoModelForCausalLM.from_pretrained(
+      base_model,
+      torch_dtype=torch.bfloat16,
+      device_map="auto",
+  )
+  tokenizer = AutoTokenizer.from_pretrained(base_model)
+  
+  sys = "Sei un an assistente AI per la lingua Italiana di nome LLaMAntino-3 ANITA " \
+      "(Advanced Natural-based interaction for the ITAlian language)." \
+      " Rispondi nella lingua usata per la domanda in modo chiaro, semplice ed esaustivo."
+  
+  messages = [
+      {"role": "system", "content": sys},
+      {"role": "user", "content": "Chi è Carlo Magno?"}
+  ]
+
+  #Method 1
+  prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+  inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+  for k,v in inputs.items():
+      inputs[k] = v.cuda()
+  outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, top_p=0.9, temperature=0.6)
+  results = tokenizer.batch_decode(outputs)[0]
+  print(results)
+
+  #Method 2
+  import transformers
+  pipe = transformers.pipeline(
+      model=model,
+      tokenizer=tokenizer,
+      return_full_text=False, # langchain expects the full text
+      task='text-generation',
+      max_new_tokens=512, # max number of tokens to generate in the output
+      temperature=0.6,  #temperature for more or less creative answers
+      do_sample=True,
+      top_p=0.9,
+  )
+
+  sequences = pipe(messages)
+  for seq in sequences:
+      print(f"{seq['generated_text']}")
+  
+  ```
+
+- Additionally, you can also use a model with **4bit quantization** to reduce the required resources at least. You can start with the code below.
+
+  ```python
+  import torch
+  from transformers import (
+      AutoModelForCausalLM,
+      AutoTokenizer,
+      BitsAndBytesConfig,
+  )
+
+  base_model = "swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA"
+  bnb_config = BitsAndBytesConfig(
+      load_in_4bit=True,
+      bnb_4bit_quant_type="nf4",
+      bnb_4bit_compute_dtype=torch.bfloat16,
+      bnb_4bit_use_double_quant=False,
+  )
+  model = AutoModelForCausalLM.from_pretrained(
+      base_model,
+      quantization_config=bnb_config,
+      device_map="auto",
+  )
+  tokenizer = AutoTokenizer.from_pretrained(base_model)
+
+  sys = "Sei un an assistente AI per la lingua Italiana di nome LLaMAntino-3 ANITA " \
+      "(Advanced Natural-based interaction for the ITAlian language)." \
+      " Rispondi nella lingua usata per la domanda in modo chiaro, semplice ed esaustivo."
+  
+  messages = [
+      {"role": "system", "content": sys},
+      {"role": "user", "content": "Chi è Carlo Magno?"}
+  ]
+
+  #Method 1
+  prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+  inputs = tokenizer(prompt, return_tensors="pt", add_special_tokens=False)
+  for k,v in inputs.items():
+      inputs[k] = v.cuda()
+  outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, top_p=0.9, temperature=0.6)
+  results = tokenizer.batch_decode(outputs)[0]
+  print(results)
+
+  #Method 2
+  import transformers
+  pipe = transformers.pipeline(
+      model=model,
+      tokenizer=tokenizer,
+      return_full_text=False, # langchain expects the full text
+      task='text-generation',
+      max_new_tokens=512, # max number of tokens to generate in the output
+      temperature=0.6,  #temperature for more or less creative answers
+      do_sample=True,
+      top_p=0.9,
+  )
+
+  sequences = pipe(messages)
+  for seq in sequences:
+      print(f"{seq['generated_text']}")
+
+  ```
+
+<hr>
+
+## Evaluation
+
+**Open LLM Leaderboard:**
+
+Evaluated with lm-evaluation-benchmark-harness for the [**Open Italian LLMs Leaderboard**](https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard)
+```
+   lm_eval --model hf --model_args pretrained=HUGGINGFACE_MODEL_ID  --tasks hellaswag_it,arc_it  --device cuda:0 --batch_size auto:2
+   lm_eval --model hf --model_args pretrained=HUGGINGFACE_MODEL_ID  --tasks m_mmlu_it --num_fewshot 5  --device cuda:0 --batch_size auto:2 
+```
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | **0.6160**  |
+| Arc_IT         | 0.5714 |
+| Hellaswag_IT    | 0.7093 |
+| MMLU_IT          | 0.5672 |
+
+<hr>
+
+## Unsloth
+
+<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" width="200px" align="center" />
+
+[Unsloth](https://unsloth.ai), a great tool that helps us easily develop products, at a lower cost than expected.
+
+## Citation instructions
+```bibtex
+@misc{polignano2024advanced,
+      title={Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA}, 
+      author={Marco Polignano and Pierpaolo Basile and Giovanni Semeraro},
+      year={2024},
+      eprint={2405.07101},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+```bibtex
+@misc{basile2023llamantino,
+      title={LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language}, 
+      author={Pierpaolo Basile and Elio Musacchio and Marco Polignano and Lucia Siciliani and Giuseppe Fiameni and Giovanni Semeraro},
+      year={2023},
+      eprint={2312.09993},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+```bibtex
+@article{llama3modelcard,
+  title={Llama 3 Model Card},
+  author={AI@Meta},
+  year={2024},
+  url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
+}
+```
+
+# Acknowledgments
+We acknowledge the support of the PNRR project [FAIR - Future AI Research (PE00000013)](https://fondazione-fair.it/en/foundation/), Spoke 6 - Symbiotic AI (CUP H97G22000210007) under the NRRP MUR program funded by the NextGenerationEU.
+Models are built on the Leonardo supercomputer with the support of CINECA-Italian Super Computing Resource Allocation, class C project IscrC\_Pro\_MRS (HP10CQO70G).
+<img src="https://wiki.u-gov.it/confluence/download/attachments/49842317/image2022-6-21_11-11-44.png?version=1&modificationDate=1655802705000&api=v2" width="600px">
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_swap-uniba__LLaMAntino-3-ANITA-8B-Inst-DPO-ITA)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |75.12|
+|AI2 Reasoning Challenge (25-Shot)|74.57|
+|HellaSwag (10-Shot)              |92.75|
+|MMLU (5-Shot)                    |66.85|
+|TruthfulQA (0-shot)              |75.93|
+|Winogrande (5-shot)              |82.00|
+|GSM8k (5-shot)                   |58.61|
+

USE_POLICY.md

@@ -0,0 +1,53 @@
+# Meta Llama 3 Acceptable Use Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Meta Llama 3. If you
+access or use Meta Llama 3, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
+this policy can be found at [https://llama.meta.com/llama3/use-policy](https://llama.meta.com/llama3/use-policy)
+
+## Prohibited Uses
+
+We want everyone to use Meta Llama 3 safely and responsibly. You agree you will not use, or allow
+others to use, Meta Llama 3 to:
+
+1. Violate the law or others’ rights, including to:
+    1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
+        1. Violence or terrorism
+        2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
+        3. Human trafficking, exploitation, and sexual violence
+        4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
+        5. Sexual solicitation
+        6. Any other criminal activity
+    2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
+    3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
+    4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
+    5. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
+    6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials
+    7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
+
+2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Meta Llama 3 related to the following:
+    1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
+    2. Guns and illegal weapons (including weapon development)
+    3. Illegal drugs and regulated/controlled substances
+    4. Operation of critical infrastructure, transportation technologies, or heavy machinery
+    5. Self-harm or harm to others, including suicide, cutting, and eating disorders
+    6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
+
+3. Intentionally deceive or mislead others, including use of Meta Llama 3 related to the following:
+    1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+    2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+    3. Generating, promoting, or further distributing spam
+    4. Impersonating another individual without consent, authorization, or legal right
+    5. Representing that the use of Meta Llama 3 or outputs are human-generated
+    6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
+
+4. Fail to appropriately disclose to end users any known dangers of your AI system
+
+Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation
+of this Policy through one of the following means:
+
+● Reporting issues with the model: [https://github.com/meta-llama/llama3](https://github.com/meta-llama/llama3)
+● Reporting risky content generated by the model:
+developers.facebook.com/llama_output_feedback
+● Reporting bugs and security concerns: facebook.com/whitehat/info
+● Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3:
+LlamaUseReport@meta.com

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special_tokens_map.json

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