--- library_name: transformers tags: [] --- # Model Card for Model ID This model is a Bits&Bytes 4 bits quantization of the https://huggingface.co/OpenLLM-Ro/RoLlama3-8b-Instruct model. The main advantages of this model are : - it runs on a GPU with 6GB of free ram. (So usually a user-grade gpu with 8 Gb VRAM, versus the standard model which needs 48+GB). - it is 2-3 times faster in inference time/token The main drawback is that is less accurate than the full(original) model, although is up to you to decide if the compromise is a good fit for your use-case. ## Model Details ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. OpenLLM-Ro represents the first open-source effort to build a LLM specialized for Romanian. OpenLLM-Ro developed and publicly releases a collection of Romanian LLMs, both in the form of foundational model and instruct and chat variants. Developed by: OpenLLM-Ro Language(s): Romanian License: cc-by-nc-4.0 Finetuned from model: Meta-Llama-3-8B-Instruct Trained using: RoAlpaca, RoAlpacaGPT4, RoDolly, RoSelfInstruct, RoNoRobots, RoOrca, RoCamel, RoOpenAssistant, RoUltraChat ### Model Sources [optional] Repository: https://github.com/OpenLLM-Ro/LLaMA-Factory Paper: https://arxiv.org/abs/2406.18266 ntended Use Intended Use Cases RoLlama3 is intented for research use in Romanian. Base models can be adapted for a variety of natural language tasks while instruction and chat tuned models are intended for assistant-like chat. Out-of-Scope Use Use in any manner that violates the license, any applicable laws or regluations, use in languages other than Romanian. How to Get Started with the Model Use the code below to get started with the model. from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoLlama3-8b-Instruct") model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama3-8b-Instruct") instruction = "Ce jocuri de societate pot juca cu prietenii mei?" chat = [ {"role": "system", "content": "Ești un asistent folositor, respectuos și onest. Încearcă să ajuți cât mai mult prin informațiile oferite, excluzând răspunsuri toxice, rasiste, sexiste, periculoase și ilegale."}, {"role": "user", "content": instruction}, ] prompt = tokenizer.apply_chat_template(chat, tokenize=False, system_message="") inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt") outputs = model.generate(input_ids=inputs, max_new_tokens=128) print(tokenizer.decode(outputs[0])) ## Academic Benchmarks
Model | |||||||
RoLlama-3-8B-Instruct-4Bit | |||||||
Llama-3-8B-Instruct | |||||||
RoLlama3-8b-Instruct-2024-06-28 | |||||||
RoLlama3-8b-Instruct-2024-10-09 | |||||||
RoLlama3-8b-Instruct-DPO-2024-10-09 |
Model | (Macro F1) |
(Macro F1) |
(Macro F1) |
(Macro F1) |
(Bleu) |
(Bleu) |
(Bleu) |
(Bleu) |
Llama-3-8B-Instruct | ||||||||
RoLlama3-8b-Instruct-2024-06-28 | ||||||||
RoLlama3-8b-Instruct-2024-10-09 | ||||||||
RoLlama3-8b-Instruct-DPO-2024-10-09 |
Model | ||||||||
RoLlama-3-8B-Instruct-4Bit - F5 Scores | ||||||||
Llama-3-8B-Instruct | ||||||||
RoLlama3-8b-Instruct-2024-06-28 | ||||||||
RoLlama3-8b-Instruct-2024-10-09 | ||||||||
RoLlama3-8b-Instruct-DPO-2024-10-09 |