Norwai Mixtral 8x7B Instruct

🚀 NorwAI-Mixtral-8x7B-instruct

NorwAI-Mixtral-8x7B-instruct is an instruction-tuned model based on NorwAI-Mixtral-8x7B, optimized with about 9000 high - quality Norwegian instructions. It's part of the NowAI LLM family, developed through a collaboration of multiple Norwegian institutions. This model aims to boost the research and applications of Norwegian language models.

🚀 Quick Start

NowAI LLM is available for both commercial and research use in Nordic countries. To access the model, carefully read the message and fill in the required information. Note that access is restricted to students, companies, and organizations from Nordic countries. Please provide your work email or student email to access the models.

✨ Features

• Instruction Tuned: Trained with around 9000 self - collected high - quality Norwegian instructions.
• Family of Models: Part of the NowAI LLM family with various model sizes (7B and 45B) and architectures.
• Vocabulary Expansion: Expanded Norwegian vocabulary by merging with the Llama 2 tokenizer.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

Basic Usage

We have two prompt templates for instruction tuning:

If we have input data, we use Prompt 1: {instruction}\n\n{inst_input}\nAnswer:

If we do not have iniput data, we use Prompt 2: {instruction}\n\nAnswer:

Advanced Usage

Let's see the following example to load the model:

from transformers import AutoTokenizer, AutoModelForCausalLM

model_and_tokenizer_path = "NorwAI/NorwAI-Mixtral-8x7B-instruct"
access_token = "<your access token>"

# import tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_and_tokenizer_path, token=access_token)
model = AutoModelForCausalLM.from_pretrained(model_and_tokenizer_path, token=access_token, device_map='balanced')

# define your own prompt
prompt = """Hvilket av de følgende alternativene er Norges nordligste punkt?\n\na) Nordkapp b) Alta c) Vardø d) Hammerfest\n
        Svar:"""

# generate response
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, 
                    min_new_tokens=50, 
                    max_new_tokens=100,
                    do_sample=True,
                    temperature=0.3)
outputs = tokenizer.decode(outputs[0], skip_special_tokens=True)

According to our test, replacing Answer with Svar can also achieve the same effect.

📚 Documentation

Model Details

• Developed by: NowAI at NTNU, Schibsted and VG
• Model type: Generative text model
• Language(s) (NLP): Norwegian
• Finetuned from model: NorwAI-Mixtral-8x7B
• Tokenizer: We expanded the Norwegian vocabulary by merging the Llama 2 tokenizer with the vocabulary from our own trained Norwegian tokenizer. The extended vocabulary size is 64000.
• Models release date: May 15, 2024 but are being continuously updated.

The NowAI LLM family is based on an auto - regressive language model architecture.

Bias, Risks, and Limitations

The model may have potential risks common to large language models, such as hallucination, factual inconsistency, toxicity, and bias etc.

🔧 Technical Details

Training Data

All NorwAI LLM models were (continue - )pretrained on 51.15 Billion tokens, equivalent to 30.33 Billion words, sourced from public datasets and data shared by Schibsted, NRK, and VG partners under agreement. The publicly available datasets were preprocessed to filter out texts with copyright issues, and all datasets were preprocessed to remove sensitive information.

Training Infrastructure

All models were pretrained and fine - tuned using the [llm - foundary framework](https://github.com/mosaicml/llm - foundry) on the IDUN cluster in NTNU.

📄 License

NorLLM License

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Contact people for technical questions: Lemei Zhang (lemei.zhang@ntnu.no), Peng Liu (peng.liu@ntnu.no)

Contact people for license questions: Jon Atle Gulla (jon.atle.gulla@ntnu.no)

Model Card Contact

If you have any questions regarding the models, please contact the following people: Lemei Zhang, lemei.zhang@ntnu.no Peng Liu, peng.liu@ntnu.no

⚠️ Important Note

Access is limited to students, companies, and organizations from Nordic countries. Kindly provide your work email or student email to access the models. Thank you for your understanding.

💡 Usage Tip

According to our test, replacing Answer with Svar in the prompt can also achieve the same effect.