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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+LLaMAntino-2-7b-hf-ITA - GGUF
+- Model creator: https://huggingface.co/swap-uniba/
+- Original model: https://huggingface.co/swap-uniba/LLaMAntino-2-7b-hf-ITA/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [LLaMAntino-2-7b-hf-ITA.Q2_K.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q2_K.gguf) | Q2_K | 2.36GB |
+| [LLaMAntino-2-7b-hf-ITA.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.IQ3_XS.gguf) | IQ3_XS | 2.6GB |
+| [LLaMAntino-2-7b-hf-ITA.IQ3_S.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.IQ3_S.gguf) | IQ3_S | 2.75GB |
+| [LLaMAntino-2-7b-hf-ITA.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q3_K_S.gguf) | Q3_K_S | 2.75GB |
+| [LLaMAntino-2-7b-hf-ITA.IQ3_M.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.IQ3_M.gguf) | IQ3_M | 2.9GB |
+| [LLaMAntino-2-7b-hf-ITA.Q3_K.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q3_K.gguf) | Q3_K | 3.07GB |
+| [LLaMAntino-2-7b-hf-ITA.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q3_K_M.gguf) | Q3_K_M | 3.07GB |
+| [LLaMAntino-2-7b-hf-ITA.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q3_K_L.gguf) | Q3_K_L | 3.35GB |
+| [LLaMAntino-2-7b-hf-ITA.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.IQ4_XS.gguf) | IQ4_XS | 3.4GB |
+| [LLaMAntino-2-7b-hf-ITA.Q4_0.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q4_0.gguf) | Q4_0 | 3.56GB |
+| [LLaMAntino-2-7b-hf-ITA.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.IQ4_NL.gguf) | IQ4_NL | 3.58GB |
+| [LLaMAntino-2-7b-hf-ITA.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q4_K_S.gguf) | Q4_K_S | 3.59GB |
+| [LLaMAntino-2-7b-hf-ITA.Q4_K.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q4_K.gguf) | Q4_K | 3.8GB |
+| [LLaMAntino-2-7b-hf-ITA.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q4_K_M.gguf) | Q4_K_M | 3.8GB |
+| [LLaMAntino-2-7b-hf-ITA.Q4_1.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q4_1.gguf) | Q4_1 | 3.95GB |
+| [LLaMAntino-2-7b-hf-ITA.Q5_0.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q5_0.gguf) | Q5_0 | 4.33GB |
+| [LLaMAntino-2-7b-hf-ITA.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q5_K_S.gguf) | Q5_K_S | 4.33GB |
+| [LLaMAntino-2-7b-hf-ITA.Q5_K.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q5_K.gguf) | Q5_K | 4.45GB |
+| [LLaMAntino-2-7b-hf-ITA.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q5_K_M.gguf) | Q5_K_M | 4.45GB |
+| [LLaMAntino-2-7b-hf-ITA.Q5_1.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q5_1.gguf) | Q5_1 | 4.72GB |
+| [LLaMAntino-2-7b-hf-ITA.Q6_K.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q6_K.gguf) | Q6_K | 5.15GB |
+| [LLaMAntino-2-7b-hf-ITA.Q8_0.gguf](https://huggingface.co/RichardErkhov/swap-uniba_-_LLaMAntino-2-7b-hf-ITA-gguf/blob/main/LLaMAntino-2-7b-hf-ITA.Q8_0.gguf) | Q8_0 | 6.67GB |
+
+
+
+
+Original model description:
+---
+license: llama2
+language:
+- it
+tags:
+- text-generation-inference
+---
+# Model Card for LLaMAntino-2-7b-ITA
+*Last Update: 22/01/2024*<br>
+
+## Model description
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+**LLaMAntino-2-7b** is a *Large Language Model (LLM)* that is an italian-adapted **LLaMA 2**. 
+This model aims to provide Italian NLP researchers with a base model for natural language generation tasks.
+
+The model was trained using *QLora* and using as training data [clean_mc4_it medium](https://huggingface.co/datasets/gsarti/clean_mc4_it/viewer/medium). 
+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
+- **Language(s) (NLP):** Italian
+- **License:** Llama 2 Community License 
+- **Finetuned from model:** [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf)
+
+## 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-2-7b-hf-ITA"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+prompt = "Scrivi qui un possibile prompt"
+
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+outputs = model.generate(input_ids=input_ids)
+
+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
+
+## 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:
+
+```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}
+}
+```
+
+*Notice:* Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. [*License*](https://ai.meta.com/llama/license/)
+