Text Generation
Transformers
Safetensors
mistral
fine-tuning
prose
KTO
axolotl
finetune
roleplaying
creative-writing
conversational
text-generation-inference
Instructions to use Delta-Vector/Rei-24B-KTO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Delta-Vector/Rei-24B-KTO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Delta-Vector/Rei-24B-KTO") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Delta-Vector/Rei-24B-KTO") model = AutoModelForCausalLM.from_pretrained("Delta-Vector/Rei-24B-KTO") 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/Rei-24B-KTO with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Delta-Vector/Rei-24B-KTO" # 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/Rei-24B-KTO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Delta-Vector/Rei-24B-KTO
- SGLang
How to use Delta-Vector/Rei-24B-KTO 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/Rei-24B-KTO" \ --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/Rei-24B-KTO", "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/Rei-24B-KTO" \ --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/Rei-24B-KTO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Delta-Vector/Rei-24B-KTO with Docker Model Runner:
docker model run hf.co/Delta-Vector/Rei-24B-KTO
| library_name: transformers | |
| tags: | |
| - fine-tuning | |
| - prose | |
| - KTO | |
| - axolotl | |
| - finetune | |
| - roleplaying | |
| - creative-writing | |
| base_model: | |
| - Delta-Vector/Rei-24B-Base | |
| <style> | |
| @import url('https://fonts.googleapis.com/css2?family=Share+Tech+Mono&display=swap'); | |
| body { | |
| font-family: 'Share Tech Mono', monospace; | |
| background: #121212; | |
| color: #E0E0E0; | |
| margin: 0; | |
| padding: 0; | |
| font-size: 16px; | |
| } | |
| .container { | |
| margin: 20px auto; | |
| background-color: #1E1E1E; | |
| padding: 20px; | |
| border-radius: 8px; | |
| box-shadow: 0 0 25px rgba(255, 0, 51, 0.3); | |
| border: 1px solid #FF0033; | |
| position: relative; | |
| max-width: 1000px; | |
| } | |
| .header h1 { | |
| font-size: 32px; | |
| color: #FF0033; | |
| margin: 0 0 20px 0; | |
| text-align: center; | |
| text-shadow: 0 0 10px rgba(255, 0, 51, 0.7); | |
| text-transform: uppercase; | |
| } | |
| .section { | |
| margin-top: 30px; | |
| } | |
| .section h2 { | |
| font-size: 26px; | |
| color: #FF0033; | |
| text-align: center; | |
| border-bottom: 1px solid #FF0033; | |
| padding-bottom: 10px; | |
| margin-bottom: 20px; | |
| } | |
| .info p { | |
| color: #E0E0E0; | |
| line-height: 1.7; | |
| font-size: 16px; | |
| } | |
| .info img { | |
| width: 100%; | |
| max-width: 600px; | |
| border-radius: 4px; | |
| margin: 0 auto 15px; | |
| display: block; | |
| box-shadow: 0 0 20px rgba(0, 0, 0, 0.5); | |
| border: 1px solid #444; | |
| } | |
| a { | |
| color: #FF0033; | |
| text-decoration: none; | |
| transition: color 0.2s ease, text-shadow 0.2s ease; | |
| } | |
| a:hover { | |
| color: #FFFFFF; | |
| text-shadow: 0 0 8px rgba(255, 0, 51, 0.8); | |
| } | |
| .button { | |
| display: inline-block; | |
| background-color: transparent; | |
| color: #FF0033; | |
| padding: 10px 20px; | |
| border-radius: 4px; | |
| cursor: pointer; | |
| text-decoration: none; | |
| border: 1px solid #FF0033; | |
| transition: background-color 0.2s ease, box-shadow 0.2s ease, color 0.2s ease; | |
| } | |
| .button:hover { | |
| background-color: #FF0033; | |
| color: #121212; | |
| box-shadow: 0 0 15px rgba(255, 0, 51, 0.7); | |
| } | |
| pre { | |
| background-color: #0d0d0d; | |
| padding: 15px; | |
| border-radius: 4px; | |
| overflow-x: auto; | |
| border: 1px solid #444; | |
| border-left: 3px solid #FF0033; | |
| color: #E0E0E0; | |
| } | |
| code { | |
| font-family: 'Share Tech Mono', monospace; | |
| color: #E0E0E0; | |
| } | |
| .info-card { | |
| background: #2a2a2a; | |
| border: 1px solid #444; | |
| border-radius: 8px; | |
| overflow: hidden; | |
| } | |
| .info-header { | |
| background: #1a1a1a; | |
| padding: 20px; | |
| border-bottom: 1px solid #444; | |
| } | |
| .info-header h3 { | |
| color: #FFFFFF; | |
| margin: 0 0 10px 0; | |
| font-size: 22px; | |
| text-align: center; | |
| } | |
| .model-tags { | |
| display: flex; | |
| justify-content: center; | |
| gap: 10px; | |
| flex-wrap: wrap; | |
| } | |
| .model-tag { | |
| background: #121212; | |
| color: #FF0033; | |
| padding: 5px 10px; | |
| border-radius: 4px; | |
| font-size: 12px; | |
| border: 1px solid #FF0033; | |
| text-transform: uppercase; | |
| } | |
| .model-composition { | |
| padding: 20px; | |
| border-bottom: 1px solid #444; | |
| } | |
| .model-composition h4 { | |
| color: #FFFFFF; | |
| margin: 0 0 15px 0; | |
| font-size: 18px; | |
| text-align: center; | |
| } | |
| .composition-list { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0; | |
| display: grid; | |
| gap: 10px; | |
| } | |
| .composition-list li { | |
| color: #E0E0E0; | |
| display: flex; | |
| align-items: baseline; | |
| gap: 8px; | |
| } | |
| .model-component { | |
| font-weight: bold; | |
| min-width: 120px; | |
| } | |
| .model-description { | |
| padding: 20px; | |
| background: #2a2a2a; | |
| } | |
| .metrics-section { | |
| margin-bottom: 30px; | |
| } | |
| .metrics-section details { | |
| background: #2a2a2a; | |
| border: 1px solid #444; | |
| border-radius: 8px; | |
| padding: 15px; | |
| margin-bottom: 15px; | |
| } | |
| .metrics-section summary { | |
| color: #FF0033; | |
| font-size: 18px; | |
| cursor: pointer; | |
| outline: none; | |
| padding: 5px 0; | |
| text-align: center; | |
| font-weight: bold; | |
| } | |
| .creator-section { | |
| margin: 20px 0; | |
| } | |
| .creator-badge { | |
| display: inline-flex; | |
| align-items: center; | |
| background: #1a1a1a; | |
| border: 1px solid #444; | |
| border-radius: 4px; | |
| padding: 10px 15px; | |
| } | |
| .creator-label { | |
| color: #E0E0E0; | |
| font-size: 14px; | |
| margin-right: 8px; | |
| } | |
| .creator-link { | |
| display: flex; | |
| align-items: center; | |
| gap: 5px; | |
| color: #FF0033; | |
| text-decoration: none; | |
| transition: all 0.2s ease; | |
| } | |
| .creator-name { | |
| font-weight: 600; | |
| } | |
| .creator-arrow { | |
| font-size: 16px; | |
| transition: transform 0.2s ease; | |
| } | |
| .creator-link:hover .creator-arrow { | |
| transform: translateX(5px); | |
| } | |
| .link-arrow { | |
| display: inline-block; | |
| transition: transform 0.2s ease; | |
| } | |
| a:hover .link-arrow { | |
| transform: translateX(5px); | |
| } | |
| .axolotl-container { | |
| text-align: center; | |
| margin: 30px 0; | |
| filter: invert(1) hue-rotate(180deg); | |
| } | |
| .axolotl-container img { | |
| max-width: 300px; | |
| border-radius: 8px; | |
| box-shadow: 0 2px 10px rgba(0, 0, 0, 0.3); | |
| border: 1px solid #000000; | |
| } | |
| </style> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Rei-KTO-24B</title> | |
| </head> | |
| <body> | |
| <div class="container"> | |
| <div class="header"> | |
| <h1>Rei-KTO-24B</h1> | |
| </div> | |
| <div class="info"> | |
| <img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F66c26b6fb01b19d8c3c2467b%2FEFNIBpVv1OITZl_su5DyR.png%26quot%3B alt="Model banner"> | |
| <div style="text-align: center;"> | |
| <div class="creator-section"> | |
| <div class="creator-badge"> | |
| <span class="creator-label">Created by</span> | |
| <a href="https://huggingface.co/Delta-Vector" target="_blank" class="creator-link"> | |
| <span class="creator-name">Delta-Vector</span> | |
| <span class="creator-arrow">→</span> | |
| </a> | |
| </div> | |
| </div> | |
| <div class="model-info"> | |
| <h2>Model Information</h2> | |
| <div class="info-card"> | |
| <div class="info-header"> | |
| <h>Rei-KTO-24B</h3> | |
| <div class="model-tags"> | |
| <span class="model-tag">KTO enhanced</span> | |
| <span class="model-tag">Painted Fantasy Finetune</span> | |
| <span class="model-tag">Creative Prose</span> | |
| </div> | |
| </div> | |
| <div class="model-description"> | |
| <p>A model meant to replicate the style and prose of the Anthropic Claude models, Opus and Sonnet. This model is meant for Roleplaying/Creative-writing, Has some nice smarts without being too sloppy, etc - It's pretty good. Trained in 2 steps, Firstly SFT trained on Zerofata's PaintedFantasy which i found great at anime-otaku-esque characters, and then KTO'd to improve coherency and Instruct Following </p> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2>Quantized Versions</h2> | |
| <div class="info-card"> | |
| <div class="model-composition"> | |
| <h4>Available Downloads</h4> | |
| <ul class="composition-list"> | |
| <li><span class="model-component"><a href="https://huggingface.co/mradermacher/Rei-24B-KTO-GGUF" target="_blank">GGUF Format</a></span>For use with LLama.cpp & Forks (Ty Mradermacher <3)</li> | |
| <li><span class="model-component"><a href="https://huggingface.co/DeathGodlike/Rei-24B-KTO_EXL3" target="_blank">EXL3 Format</a></span>For use with TabbyAPI</li> | |
| </ul> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2>Prompting</h2> | |
| <p>The model is tuned with V7 Tekken formatting. A typical input would look like this:</p> | |
| <pre><code><span style="color:#FF0033;"><s>[SYSTEM_PROMPT]system_prompt[/SYSTEM_PROMPT][INST]Hi there![/INST]Nice to meet you!</s>[INST]Can I ask a question?[/INST] | |
| </code></pre> | |
| </div> | |
| <div class="section"> | |
| <h2>Training</h2> | |
| <p>Training was done in 2 steps, SFT>KTO</p> | |
| <div class="metrics-section"> | |
| <details> | |
| <summary>Access Configs</summary> | |
| <pre><code> SFT: https://wandb.ai/new-eden/Painted-Fantasy-Rei/artifacts/axolotl-config/config-u7to9d5q/v0/files/axolotl_config_f0p7vnaf.yml | |
| KTO : https://wandb.ai/new-eden/Painted-Rei/artifacts/axolotl-config/config-8n37w77c/v0/files/axolotl_config_hvrd2tzn.yml | |
| </code></pre> | |
| </details> | |
| </div> | |
| </div> | |
| <div class="section"> | |
| <h2>Training</h2> | |
| <p>The training was done for 2 epochs using 8 x A100s for 24 hours/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>Thank you to <a href="https://huggingface.co/lucyknada">Lucy Knada</a>, <a href="https://huggingface.co/Ateron">Ateron</a>, <a href="https://huggingface.co/AliCat2">Alicat</a>, <a href="https://huggingface.co/intervitens">Intervitens</a>, <a href="https://huggingface.co/cgato">Cgato</a>, <a href="https://huggingface.co/kubernetes-bad">Kubernetes Bad</a> and the rest of <a href="https://huggingface.co/anthracite-org">Anthracite</a>.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </body> | |
| </html> |