Instructions to use SZLHOLDINGS/chaski with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SZLHOLDINGS/chaski with Transformers:

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

pipe = pipeline("text-generation", model="SZLHOLDINGS/chaski")
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("SZLHOLDINGS/chaski")
model = AutoModelForMultimodalLM.from_pretrained("SZLHOLDINGS/chaski", device_map="auto")
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 SZLHOLDINGS/chaski with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/SZLHOLDINGS/chaski

SGLang

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

Docker Model Runner
How to use SZLHOLDINGS/chaski with Docker Model Runner:
```
docker model run hf.co/SZLHOLDINGS/chaski
```

C H A S K I

The courier that cannot invent the dispatch.

RESEARCH / NEGATIVE EVIDENCE. Failed qualification. Not flagship. The current Named-N run failed both release gates. This card does not promote the model, its later SKUs, or any live endpoint.

Contract

Chaski is an SZL fine-tune of the disclosed Apache-2.0 base Qwen/Qwen3.5-0.8B. It produces proposal-only drafts behind a validating controller. The model does not execute actions, authorize mutations, or convert uncertainty into a fact.

No uniqueness claim is made. The value of this artifact is its explicit controller boundary, disclosed lineage, and retained negative evidence.

Field	Verified statement
Artifact	Merged fine-tune plus LoRA artifacts are present on the Hub repository
Parent/eval revision	`1c55df8652e9d0f7b84356b1e2d54849165ae884`
Base relation	`finetune`; `artifact_class: MERGED_FINETUNE`
Originality	`FINETUNE_DISCLOSED_BASE`
Publication eligibility	`false`
Autonomy eligibility	`false`
Lambda	Conjecture 1, advisory and never a theorem
Trust ceiling	`0.97`

Canonical source: szl-holdings/szl-forge/chaski/card. Exact publication source and asset hashes are recorded in szl-source-binding.json on this model repository.

Evaluation

Named-N: MEASURED FAIL. The measured run on 2026-08-28 is a failed gate, not a passing benchmark.

Probe	Result	Interpretation
JSON draft	0/5	failed
Adversarial refusal	2/6	failed
Hallucinated citations	0 observed in this bounded run	not a general guarantee

Receipt: eval_report.json, 3996 bytes, SHA-256 4d057eb9867285e69b00222be110bbb660330a96fe7b284a4d7f488268a13e05, source commit db71c243d0176bccff1ff087cd4dd57663bd6502.

Method: in-process greedy generation over messages[:-1], Transformers 5.16.1, bf16 CPU, load_in_4bit=False. This evidence does not transfer to A11OY-MINI, another revision, another runtime, or another prompt set.

Loading

The repository contains multiple loadable forms. Select the intended artifact explicitly rather than relying on loader precedence.

from transformers import AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "SZLHOLDINGS/chaski",
    trust_remote_code=False,
)

For the LoRA path, load Qwen/Qwen3.5-0.8B first and attach the adapter with PEFT. The root contains both config.json and adapter_config.json; callers must verify which path their library selects. The merged shard uses a non-standard filename resolved through its index.

Intended use

Proposal-only JSON drafts with approvalRequired=true and executed=false.
Doctrine-faithful abstention and routing experiments.
Research behind an independent validator and human approval boundary.

Prohibited interpretation

Not an autonomous agent, executor, factual oracle, or weapons system.
Not a passing 5/5 or 6/6 release.
Not evidence of a deployed Alloy endpoint.
Not evidence that a later SKU inherits this evaluation.
Lab load forbidden for Chaski.

Limitations

Narrow curriculum, small bounded evaluation, CPU-only measured run, and failed release gates. A new model or runtime revision requires a new immutable evaluation receipt; this card cannot confer approval.

Doctrine v11 LOCKED. Λ = Conjecture 1. Owner: Stephen Lutar / SZL Holdings.