Instructions to use Auroraventures/cipher-sft-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Auroraventures/cipher-sft-merged with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Auroraventures/cipher-sft-merged")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Auroraventures/cipher-sft-merged")
model = AutoModelForMultimodalLM.from_pretrained("Auroraventures/cipher-sft-merged")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Auroraventures/cipher-sft-merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Auroraventures/cipher-sft-merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Auroraventures/cipher-sft-merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Auroraventures/cipher-sft-merged

SGLang

How to use Auroraventures/cipher-sft-merged 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 "Auroraventures/cipher-sft-merged" \
    --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": "Auroraventures/cipher-sft-merged",
		"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 "Auroraventures/cipher-sft-merged" \
        --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": "Auroraventures/cipher-sft-merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use Auroraventures/cipher-sft-merged with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Auroraventures/cipher-sft-merged to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Auroraventures/cipher-sft-merged to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Auroraventures/cipher-sft-merged to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Auroraventures/cipher-sft-merged",
    max_seq_length=2048,
)

Docker Model Runner
How to use Auroraventures/cipher-sft-merged with Docker Model Runner:
```
docker model run hf.co/Auroraventures/cipher-sft-merged
```

Auroraventures commited on Apr 14

Commit

b1489f9

verified ·

1 Parent(s): e77e8d8

Upload quickgen.py with huggingface_hub

Browse files

Files changed (1) hide show

quickgen.py +11 -10

quickgen.py CHANGED Viewed

@@ -1,15 +1,16 @@
-"""Generate 3 Awwwards-quality website examples with Cipher SFT."""
 import torch, re, os
-from transformers import AutoModelForCausalLM, AutoTokenizer
-print("[1/4] Loading tokenizer...", flush=True)
-tok = AutoTokenizer.from_pretrained("/content/cipher-sft-merged")
-print("[2/4] Loading model (60GB - takes ~2min)...", flush=True)
-m = AutoModelForCausalLM.from_pretrained(
-    "/content/cipher-sft-merged",
-    torch_dtype=torch.bfloat16,
-    device_map="auto",
 )
 PROMPTS = {
     "01-hero-particles": "Build a complete single-file HTML page with a stunning hero section featuring a Three.js particle system that responds to mouse movement. Include CDN imports for Three.js (use https://unpkg.com/three@0.160.0/build/three.module.js with importmap). Use GSAP from CDN for the headline entrance animation. Style with custom CSS - dark theme with bioluminescent blue/purple accents (#9bf, #a4f). Include a headline 'Cipher.ai' and subheadline 'The Code Kraken sees what others miss.' Make it Awwwards-quality. Output ONLY the complete HTML, nothing else.",
@@ -30,7 +31,7 @@ for name, prompt in PROMPTS.items():
         msgs, tokenize=True, add_generation_prompt=True, return_tensors="pt"
     ).to("cuda")
     with torch.no_grad():
-        out = m.generate(
             inputs, max_new_tokens=4096, do_sample=True,
             temperature=0.7, top_p=0.9, repetition_penalty=1.05,
             pad_token_id=tok.eos_token_id,

+"""Generate 3 Awwwards-quality website examples with Cipher SFT (via Unsloth)."""
 import torch, re, os
+from unsloth import FastLanguageModel
+print("[1/4] Loading model with Unsloth (60GB - takes ~2min)...", flush=True)
+model, tok = FastLanguageModel.from_pretrained(
+    model_name="/content/cipher-sft-merged",
+    max_seq_length=8192,
+    load_in_4bit=True,
+    dtype=None,
 )
+FastLanguageModel.for_inference(model)
+print("[2/4] Model ready.", flush=True)
 PROMPTS = {
     "01-hero-particles": "Build a complete single-file HTML page with a stunning hero section featuring a Three.js particle system that responds to mouse movement. Include CDN imports for Three.js (use https://unpkg.com/three@0.160.0/build/three.module.js with importmap). Use GSAP from CDN for the headline entrance animation. Style with custom CSS - dark theme with bioluminescent blue/purple accents (#9bf, #a4f). Include a headline 'Cipher.ai' and subheadline 'The Code Kraken sees what others miss.' Make it Awwwards-quality. Output ONLY the complete HTML, nothing else.",
         msgs, tokenize=True, add_generation_prompt=True, return_tensors="pt"
     ).to("cuda")
     with torch.no_grad():
+        out = model.generate(
             inputs, max_new_tokens=4096, do_sample=True,
             temperature=0.7, top_p=0.9, repetition_penalty=1.05,
             pad_token_id=tok.eos_token_id,