rax-3.5-chat / model_card.md

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metadata

license: apache-2.0
language:
  - en
pipeline_tag: text-generation
tags:
  - chat
  - conversational
  - llama
  - fine-tuned
  - rax
  - raxcore
model_type: llama

Rax 3.5 Chat

Developed by RaxCore - A leading developer company in Africa and beyond

Model Description

Rax 3.5 Chat is an extensively enhanced conversational AI model featuring breakthrough improvements developed by RaxCore. Built upon the Llama architecture with TinyLlama as foundation, this model incorporates proprietary optimization techniques, advanced training methodologies, and cultural context awareness that significantly exceed baseline performance.

Quick Start

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rax-3.5-chat")
model = AutoModelForCausalLM.from_pretrained("rax-3.5-chat")

messages = [
    {"role": "system", "content": "You are Rax, a helpful AI assistant."},
    {"role": "user", "content": "Hello!"}
]

input_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)

Model Details

Architecture: Enhanced Llama (1.1B parameters with RaxCore optimizations)
Context Length: 2048 tokens
Development: Extensively enhanced by RaxCore with proprietary improvements
Base: TinyLlama foundation with significant RaxCore upgrades
License: Apache 2.0

Intended Use

Conversational AI applications
Research and educational purposes
Creative writing assistance
Chatbot development

Limitations

2048 token context limit
May generate biased or incorrect information
Requires responsible deployment practices

raxcore-dev
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rax-3.5-chat