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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- generator |
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model-index: |
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- name: DanteLLM_instruct_7b-v0.2-boosted |
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results: [] |
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library_name: peft |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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## DanteLLM |
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DanteLLM is a Large Language Model developed in Sapienza lab. |
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In October 2023 we submitted a paper called DanteLLM: Let's Push Italian LLM Research Forward! |
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🤌 🇮🇹 |
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That paper got accepted with the scores 5, 4, 4 out of 5 |
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## How to run the model (Ollama) |
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This repo contains the model in GGUF format. You can run DanteLLM on Ollama following these steps: |
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Make sure you have Ollama correctly installed and ready to use. |
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Then, you can download DanteLLM's weights using: |
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``` |
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huggingface-cli download rstless-research/DanteLLM-7B-Instruct-Italian-v0.1-GGUF dantellm-merged-hf.q8_0.gguf Modelfile --local-dir . --local-dir-use-symlinks False |
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``` |
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Load the model using: |
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``` |
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ollama create dante -f Modelfile |
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``` |
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Finally, to run the model, use: |
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``` |
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ollama run dante |
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``` |
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# Authors |
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- Andrea Bacciu* (work done prior joining Amazon) |
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- Cesare Campagnano* |
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- Giovanni Trappolini |
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- Prof. Fabrizio Silvestri |
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\* Equal contribution |
