Text Generation
Transformers
Safetensors
English
mistral
roleplay
finetune
axolotl
adventure
creative-writing
Mistral
24B
conversational
text-generation-inference
Instructions to use Delta-Vector/Austral-24B-Winton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Delta-Vector/Austral-24B-Winton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Delta-Vector/Austral-24B-Winton") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Delta-Vector/Austral-24B-Winton") model = AutoModelForCausalLM.from_pretrained("Delta-Vector/Austral-24B-Winton", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Delta-Vector/Austral-24B-Winton with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Delta-Vector/Austral-24B-Winton" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Delta-Vector/Austral-24B-Winton", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Delta-Vector/Austral-24B-Winton
- SGLang
How to use Delta-Vector/Austral-24B-Winton with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Delta-Vector/Austral-24B-Winton" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Delta-Vector/Austral-24B-Winton", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Delta-Vector/Austral-24B-Winton" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Delta-Vector/Austral-24B-Winton", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Delta-Vector/Austral-24B-Winton with Docker Model Runner:
docker model run hf.co/Delta-Vector/Austral-24B-Winton
| license: apache-2.0 | |
| base_model: | |
| - Delta-Vector/Austral-SFT-KTO | |
| language: | |
| - en | |
| library_name: transformers | |
| tags: | |
| - roleplay | |
| - finetune | |
| - axolotl | |
| - adventure | |
| - creative-writing | |
| - Mistral | |
| - 24B | |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Austral 24B Winton</title> | |
| <link href="" rel="stylesheet"> | |
| <style> | |
| body { | |
| font-family: 'Roboto Slab', serif; | |
| background: linear-gradient(135deg, #8B4513 0%, #A0522D 25%, #CD853F 50%, #D2691E 75%, #8B4513 100%); | |
| background-size: 400% 400%; | |
| animation: prehistoricShift 20s ease-in-out infinite; | |
| color: #2F1B14; | |
| margin: 0; | |
| padding: 0; | |
| font-size: 16px; | |
| min-height: 100vh; | |
| } | |
| @keyframes prehistoricShift { | |
| 0%, 100% { background-position: 0% 50%; } | |
| 50% { background-position: 100% 50%; } | |
| } | |
| .container { | |
| margin: 20px; | |
| background: linear-gradient(145deg, #F4E4BC 0%, #DEB887 100%); | |
| padding: 20px; | |
| border-radius: 15px; | |
| box-shadow: 0 8px 25px rgba(0, 0, 0, 0.4), inset 0 2px 5px rgba(255, 255, 255, 0.3); | |
| border: 4px solid #8B4513; | |
| position: relative; | |
| overflow: hidden; | |
| } | |
| .container::before { | |
| content: ''; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| right: 0; | |
| bottom: 0; | |
| background-image: | |
| radial-gradient(circle at 20% 80%, rgba(139, 69, 19, 0.1) 0%, transparent 50%), | |
| radial-gradient(circle at 80% 20%, rgba(160, 82, 45, 0.1) 0%, transparent 50%); | |
| pointer-events: none; | |
| } | |
| .header h1 { | |
| font-family: 'Cinzel', serif; | |
| font-size: 32px; | |
| color: #5D2E0C; | |
| margin: 0 0 20px 0; | |
| text-align: center; | |
| text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3); | |
| letter-spacing: 2px; | |
| position: relative; | |
| } | |
| .section { | |
| margin-top: 30px; | |
| position: relative; | |
| } | |
| .section h2 { | |
| font-family: 'Cinzel', serif; | |
| font-size: 26px; | |
| color: #5D2E0C; | |
| text-align: center; | |
| margin-bottom: 20px; | |
| text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2); | |
| letter-spacing: 1px; | |
| } | |
| .info p { | |
| color: #2F1B14; | |
| line-height: 1.7; | |
| font-size: 16px; | |
| text-shadow: 0 1px 1px rgba(255, 255, 255, 0.5); | |
| } | |
| .info img { | |
| width: 85%; | |
| border-radius: 12px; | |
| margin: 0 auto 15px; | |
| display: block; | |
| box-shadow: 0 0 25px rgba(0, 0, 0, 0.4); | |
| border: 3px solid #8B4513; | |
| filter: sepia(20%) contrast(110%); | |
| } | |
| a { | |
| color: #5D2E0C; | |
| text-decoration: none; | |
| transition: all 0.3s ease; | |
| font-weight: 500; | |
| } | |
| a:hover { | |
| color: #8B4513; | |
| text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2); | |
| } | |
| .button { | |
| display: inline-block; | |
| background: linear-gradient(145deg, #CD853F, #D2691E); | |
| color: #2F1B14; | |
| padding: 12px 24px; | |
| border-radius: 8px; | |
| cursor: pointer; | |
| text-decoration: none; | |
| transition: all 0.3s ease; | |
| box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2); | |
| border: 2px solid #8B4513; | |
| } | |
| .button:hover { | |
| background: linear-gradient(145deg, #D2691E, #CD853F); | |
| box-shadow: 0 6px 15px rgba(139, 69, 19, 0.4); | |
| transform: translateY(-2px); | |
| } | |
| pre { | |
| background: linear-gradient(145deg, #F5DEB3, #DEB887); | |
| padding: 20px; | |
| border-radius: 8px; | |
| overflow-x: auto; | |
| border: 2px solid #8B4513; | |
| box-shadow: inset 0 2px 5px rgba(0, 0, 0, 0.1); | |
| } | |
| code { | |
| font-family: 'Courier New', monospace; | |
| color: #2F1B14; | |
| } | |
| .info-card { | |
| background: linear-gradient(145deg, #F5DEB3, #DEB887); | |
| border: 3px solid #8B4513; | |
| border-radius: 12px; | |
| overflow: hidden; | |
| box-shadow: 0 6px 15px rgba(0, 0, 0, 0.2); | |
| } | |
| .info-header { | |
| background: linear-gradient(145deg, #CD853F, #D2691E); | |
| padding: 25px; | |
| border-bottom: 2px solid #8B4513; | |
| } | |
| .info-header h3 { | |
| font-family: 'Cinzel', serif; | |
| color: #2F1B14; | |
| margin: 0 0 15px 0; | |
| font-size: 22px; | |
| text-align: center; | |
| text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2); | |
| letter-spacing: 1px; | |
| } | |
| .model-tags { | |
| display: flex; | |
| gap: 10px; | |
| flex-wrap: wrap; | |
| justify-content: center; | |
| } | |
| .model-tag { | |
| background: linear-gradient(145deg, #DEB887, #CD853F); | |
| color: #2F1B14; | |
| padding: 6px 12px; | |
| border-radius: 6px; | |
| font-size: 12px; | |
| border: 2px solid #8B4513; | |
| font-weight: 500; | |
| box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); | |
| } | |
| .model-composition { | |
| padding: 25px; | |
| border-bottom: 2px solid #8B4513; | |
| } | |
| .model-composition h4 { | |
| font-family: 'Cinzel', serif; | |
| color: #5D2E0C; | |
| margin: 0 0 20px 0; | |
| font-size: 18px; | |
| text-align: center; | |
| letter-spacing: 1px; | |
| } | |
| .composition-list { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0; | |
| display: grid; | |
| gap: 15px; | |
| } | |
| .composition-list li { | |
| color: #2F1B14; | |
| display: flex; | |
| align-items: baseline; | |
| gap: 12px; | |
| padding: 10px; | |
| background: rgba(245, 222, 179, 0.5); | |
| border-radius: 6px; | |
| border-left: 4px solid #8B4513; | |
| } | |
| .model-component { | |
| font-weight: 600; | |
| min-width: 120px; | |
| } | |
| .model-description { | |
| padding: 25px; | |
| background: linear-gradient(145deg, #F5DEB3, #F4E4BC); | |
| } | |
| .metrics-section { | |
| margin-bottom: 30px; | |
| } | |
| .metrics-section details { | |
| background: linear-gradient(145deg, #F5DEB3, #DEB887); | |
| border: 3px solid #8B4513; | |
| border-radius: 10px; | |
| padding: 20px; | |
| margin-bottom: 20px; | |
| box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2); | |
| } | |
| .metrics-section summary { | |
| font-family: 'Cinzel', serif; | |
| color: #5D2E0C; | |
| font-size: 18px; | |
| cursor: pointer; | |
| outline: none; | |
| padding: 10px 0; | |
| text-align: center; | |
| font-weight: 500; | |
| letter-spacing: 1px; | |
| } | |
| .creator-section { | |
| margin: 25px 0; | |
| text-align: center; | |
| } | |
| .creator-badge { | |
| display: inline-flex; | |
| align-items: center; | |
| background: linear-gradient(145deg, #CD853F, #D2691E); | |
| border: 3px solid #8B4513; | |
| border-radius: 10px; | |
| padding: 15px 20px; | |
| box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2); | |
| } | |
| .creator-label { | |
| color: #2F1B14; | |
| font-size: 14px; | |
| margin-right: 10px; | |
| font-weight: 500; | |
| } | |
| .creator-link { | |
| display: flex; | |
| align-items: center; | |
| gap: 8px; | |
| color: #2F1B14; | |
| text-decoration: none; | |
| transition: all 0.3s ease; | |
| } | |
| .creator-name { | |
| font-weight: 600; | |
| } | |
| .creator-arrow { | |
| font-size: 16px; | |
| transition: transform 0.3s ease; | |
| } | |
| .creator-link:hover .creator-arrow { | |
| transform: translateX(5px); | |
| } | |
| .link-arrow { | |
| display: inline-block; | |
| transition: transform 0.3s ease; | |
| } | |
| a:hover .link-arrow { | |
| transform: translateX(3px); | |
| } | |
| .axolotl-container { | |
| text-align: center; | |
| margin: 35px 0; | |
| } | |
| .axolotl-container img { | |
| max-width: 300px; | |
| border-radius: 10px; | |
| box-shadow: 0 6px 15px rgba(0, 0, 0, 0.3); | |
| border: 3px solid #8B4513; | |
| filter: sepia(30%) contrast(110%); | |
| } | |
| .fossil-texture { | |
| position: relative; | |
| } | |
| .fossil-texture::after { | |
| content: ''; | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| right: 0; | |
| bottom: 0; | |
| background-image: | |
| radial-gradient(circle at 25% 25%, rgba(139, 69, 19, 0.05) 2px, transparent 2px), | |
| radial-gradient(circle at 75% 75%, rgba(160, 82, 45, 0.05) 1px, transparent 1px); | |
| background-size: 50px 50px, 30px 30px; | |
| pointer-events: none; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <div class="container fossil-texture"> | |
| <div class="header"> | |
| <h1>Austral 24B Winton</h1> | |
| </p> | |
| </div> | |
| <div class="info"> | |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/66c26b6fb01b19d8c3c2467b/jxUvuFK1bdOdAPiYIcBW5.jpeg" alt="Model banner"> | |
| <div style="text-align: center;"> | |
| <div class="creator-section"> | |
| <div class="creator-badge"> | |
| <span class="creator-label">Trained by</span> | |
| <a href="https://huggingface.co/Delta-Vector" target="_blank" class="creator-link"> | |
| <span class="creator-name">Delta-Vector</span> | |
| </a> | |
| </div> | |
| </div> | |
| <div class="model-info"> | |
| <h2>Overview</h2> | |
| <div class="info-card"> | |
| <div class="info-header"> | |
| <h3>Austral 24B - Winton</h3> | |
| <div class="model-tags"> | |
| <span class="model-tag">Harbinger Finetune</span> | |
| <span class="model-tag">Mistral Based</span> | |
| <span class ="model-tag">KTO enhanced</span> | |
| <span class ="model-tag">Adventure/Roleplay generalist</span> | |
| <span class="model-tag">24B Sized model</span> | |
| </div> | |
| </div> | |
| <div class="model-description"> | |
| <p style="font-weight: bold; font-style: italic;">More than 1.5-metres tall, about six-metres long and up to 1000-kilograms heavy, Australovenator Wintonensis was a fast and agile hunter. The largest known Australian theropod.</p> | |
| <p>This is a finetune of Harbinger 24B to be a generalist Roleplay/Adventure model. I've removed some of the "slops" that i noticed in an otherwise great model aswell as improving the general writing of the model, This was a multi-stage finetune, all previous checkpoints are released aswell.</p> | |
| <p>Support my finetunes / Me on Kofi: https://Ko-fi.com/deltavector | Thank you to Auri for helping/Testing ♥</p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2>Quants</h2> | |
| <div class="info-card"> | |
| <div class="model-composition"> | |
| <h4>Quants Formats</h4> | |
| <ul class="composition-list"> | |
| <li><span class="model-component"><a href="https://huggingface.co/bartowski/Delta-Vector_Austral-24B-Winton-GGUF" target="_blank">GGUF</a></span>For use with LLama.cpp & Forks (Thank Auri & Bart! <3)</li> | |
| <li><span class="model-component"><a href="https://huggingface.co/ArtusDev/Delta-Vector_Austral-24B-Winton-EXL3" target="_blank">EXL3</a></span>For use with TabbyAPI (Ty Auri and Artus!)</li> | |
| <li><span class="model-component"><a href="https://huggingface.co/ArtusDev/Delta-Vector_Austral-24B-Winton-EXL2" target="_blank">EXL2</a></span>For use with Tabby - Faster on Ampere.</li> | |
| </ul> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2>Chat Format</h2> | |
| <p>This model utilizes ChatML.</p> | |
| <pre><code><|im_start|>user | |
| Hi there!<|im_end|> | |
| <|im_start|>assistant | |
| Nice to meet you!<|im_end|> | |
| <|im_start|>user | |
| Can I ask a question?<|im_end|> | |
| <|im_start|>assistant</code></pre> | |
| </div> | |
| <div class="section"> | |
| <h2>Training</h2> | |
| <p>As the the Austral/Francois tradition, I built off another great finetune Harbinger-24B, I did 4 epochs ontop with roughly the same datamix as Francois-Huali/Austral 70B as a R128 Lora, then KTO alignment with a mix of Instruct/Small writing datasets and then finally another 4 epoch SFT with Rep_remover (Thanks Pocket!)</p> | |
| <div class="metrics-section"> | |
| <details> | |
| <summary>Config(Post-KTO SFT)</summary> | |
| <pre><code>https://wandb.ai/new-eden/austral/artifacts/axolotl-config/config-0tzehrhe/v0/files/axolotl_config_m8018fm4.yml</code></pre> | |
| </details> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2Fossil Formation Process</h2> | |
| <p>This model was trained over 4 epochs using 8 x A100s for the base SFT, Then i used KTO to clean up some coherency issues for 1 epoch, then finally training for another 4 epochs on Rep_Remover to delete slops. Total was roughly 80 hours total.</p> | |
| <p style="text-align: center; margin-top: 20px;"> | |
| <div class="axolotl-container"> | |
| <a href="https://github.com/OpenAccess-AI-Collective/axolotl" target="_blank"> | |
| <img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl"> | |
| </a> | |
| </div> | |
| <div class="section"> | |
| <h2>Credits</h2> | |
| <p>TYSM to my friends: Auri, Lucy, Trappu, Alicat, Kubernetes Bad, Intervitens, NyxKrage & Kalomaze</p> | |
| </p> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </body> | |
| </html> |