Instructions to use mediusware-ai/intellix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use mediusware-ai/intellix with PEFT:
```
Task type is invalid.
```

How to use mediusware-ai/intellix with Transformers:

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

pipe = pipeline("text-generation", model="mediusware-ai/intellix")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mediusware-ai/intellix")
model = AutoModelForCausalLM.from_pretrained("mediusware-ai/intellix", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mediusware-ai/intellix with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/mediusware-ai/intellix

SGLang

How to use mediusware-ai/intellix 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 "mediusware-ai/intellix" \
    --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": "mediusware-ai/intellix",
		"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 "mediusware-ai/intellix" \
        --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": "mediusware-ai/intellix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mediusware-ai/intellix with Docker Model Runner:
```
docker model run hf.co/mediusware-ai/intellix
```

mediusware-ai commited on Mar 30

Commit

f6694e7

verified ·

1 Parent(s): 1d2f8ad

Upload adapter_config.json with huggingface_hub

Browse files

Files changed (1) hide show

adapter_config.json +3 -3

adapter_config.json CHANGED Viewed

@@ -3,11 +3,11 @@
   "alpha_pattern": {},
   "arrow_config": null,
   "auto_mapping": {
-    "base_model_class": "Qwen3_5ForConditionalGeneration",
-    "parent_library": "transformers.models.qwen3_5.modeling_qwen3_5",
     "unsloth_fixed": true
   },
-  "base_model_name_or_path": "unsloth/Qwen3.5-2B",
   "bias": "none",
   "corda_config": null,
   "ensure_weight_tying": false,

   "alpha_pattern": {},
   "arrow_config": null,
   "auto_mapping": {
+    "base_model_class": "IntellixForConditionalGeneration",
+    "parent_library": "transformers.models.intellix.modeling_intellix",
     "unsloth_fixed": true
   },
+  "base_model_name_or_path": "mediusware/intellix-foundation",
   "bias": "none",
   "corda_config": null,
   "ensure_weight_tying": false,