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README.md

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+---
+language:
+- es
+tags:
+- conversational
+- llama2
+---
+LlamaDos is a model oriented to have conversations in Spanish. It results from a finetuning of the Llama2-7b model by Meta using various optimization techniques such as LoRa, quantization, gradient accumulation and much more.
+
+This has allowed the training to be performed on a single consumer graph (RTX 3090). More specifically, more than 250,000 conversational data were used and the training took approximately 140 hours.
+
+More info on github: https://github.com/Garrachonr/LlamaDos
+
+The training has been performed following the original data structure of the Llama2 paper, so it is recommended to follow the same structure for inference:
+
+```python
+<s>[INST] <<SYS>>
+{{ You are a helpful, respectful and honest conversational assistant. Have a conversation with the user in a natural way.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. }}
+<</SYS>>
+
+{{ user_msg_1 }} [/INST] {{ model_answer_1 }} </s><s>[INST] {{ user_msg_2 }} [/INST] {{ model_answer_1 }} </s>
+```
+
+In order to use this model:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+base_model = AutoModelForCausalLM.from_pretrained(
+    "garrachonr/llamaDos",
+    low_cpu_mem_usage=True,
+    return_dict=True,
+    torch_dtype=torch.float16,
+    device_map=device_map,
+)
+tokenizer = AutoTokenizer.from_pretrained("garrachonr/llamaDos", trust_remote_code=True)
+tokenizer.pad_token = tokenizer.eos_token
+tokenizer.padding_side = "right"
+
+# Run text generation pipeline with llamaDos
+system_prompt = "You are a helpful, respectful and honest conversational assistant. Have a conversation with the user in a natural way.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature."
+prompt1 = "Acabo de adoptar un perro"
+prompt2 = "Muy buena decisión, te gustan los perros?"
+prompt3 = "Si, cuando era pequeño tenía uno y ahora he podido adoptar otro"
+text = "<s>[INST] <<SYS>> {} <</SYS>> {} [/INST] {} </s><s>[INST] {} [/INST]".format(system_prompt, prompt1, prompt2, prompt3)
+pipe = pipeline(task="text-generation", model=base_model, tokenizer=tokenizer, max_length=200)
+result = pipe(text)
+print(result[0]['generated_text'])
+```
+
+
+This work is funded by the Comunidad de Madrid through the call Research Grants for Young Investigators from Universidad Politécnica de Madrid (GENIUS:APOYO-JOVENES-21-TAXTYC-32-K61X37), and supported by the following projects: European Commission through Project ASTOUND (101071191–-HORIZON-EIC-2021-PATHFINDERCHALLENGES-01) and BEWORD (PID2021-126061OB-C43) funded by
+MCIN/AEI/10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the
+“European Union”.
+
+We also want to give thanks to MS Azure services (especially to Irving Kwong) for their sponsorship to translate into Spanish all dialogue databases.