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
```

betterwithage commited on 2 days ago

Commit

72fb4f5

verified ·

1 Parent(s): bef153f

docs: job id is 6a91ba00 RUNNING; 6a91b8ba and 6a91b990 MEASURED failed; keep CUTTING

Browse files

Files changed (1) hide show

README.md +8 -4

README.md CHANGED Viewed

@@ -21,8 +21,11 @@ szl:
   originality: FINETUNE_DISCLOSED_BASE
   collection: "SZL Fall 2026 — Original Cuts"
   jobs: RUNNING
-  job_id: 6a91b8ba984507d9db4ea071
   job_namespace: SZLHOLDINGS
 ---
 # Chaski
@@ -35,7 +38,7 @@ szl:
 | **Originality** | SZL fine-tune of a disclosed Apache Qwen instruct base |
 | **Base** | `Qwen/Qwen3.5-0.8B` (Apache-2.0, 0.6B–2B lock) |
 | **License** | `apache-2.0` |
-| **HF Jobs** | RUNNING `6a91b8ba984507d9db4ea071` under `SZLHOLDINGS`. Not MEASURED. No serve pin. |
 | **Status** | CUTTING · train in flight · weights ROADMAP |
 | **Later SKU** | `A11OY-MINI` will be a GGUF of **this** model after train. ROADMAP. Not Khipu. |
 | **Sibling** | [`szl-receiptagent-qwen35-0.8b-v2`](https://huggingface.co/SZLHOLDINGS/szl-receiptagent-qwen35-0.8b-v2) |
@@ -62,9 +65,10 @@ The house CPU lab serves **Khipu GGUF**, not Chaski. Cite that pin only on Khipu
 ## Training
-- **Recipe:** Unsloth QLoRA SFT. Script: `train_chaski.py`.
 - **Data:** `SZLHOLDINGS/szl-1-doctrine-sft` (41 MEASURED rows) plus ouroboros identity turns. Brain corpus excluded.
-- **Job:** `6a91b8ba984507d9db4ea071` namespace `SZLHOLDINGS`. RUNNING. Train receipt absent until finish.
 ## Limitations

   originality: FINETUNE_DISCLOSED_BASE
   collection: "SZL Fall 2026 — Original Cuts"
   jobs: RUNNING
+  job_id: 6a91ba00984507d9db4ea07f
   job_namespace: SZLHOLDINGS
+  job_prior_failed:
+    - 6a91b8ba984507d9db4ea071
+    - 6a91b990984507d9db4ea077
 ---
 # Chaski
 | **Originality** | SZL fine-tune of a disclosed Apache Qwen instruct base |
 | **Base** | `Qwen/Qwen3.5-0.8B` (Apache-2.0, 0.6B–2B lock) |
 | **License** | `apache-2.0` |
+| **HF Jobs** | RUNNING [`6a91ba00984507d9db4ea07f`](https://huggingface.co/jobs/SZLHOLDINGS/6a91ba00984507d9db4ea07f) under `SZLHOLDINGS`. Not MEASURED. No serve pin. |
 | **Status** | CUTTING · train in flight · weights ROADMAP |
 | **Later SKU** | `A11OY-MINI` will be a GGUF of **this** model after train. ROADMAP. Not Khipu. |
 | **Sibling** | [`szl-receiptagent-qwen35-0.8b-v2`](https://huggingface.co/SZLHOLDINGS/szl-receiptagent-qwen35-0.8b-v2) |
 ## Training
+- **Recipe:** Unsloth QLoRA SFT. Script: `train_chaski.py`. Loads **only** `szl_dataset.jsonl` (does not `load_dataset` the whole repo; `SZL_ESTATE_MANAGED.json` is not training data).
 - **Data:** `SZLHOLDINGS/szl-1-doctrine-sft` (41 MEASURED rows) plus ouroboros identity turns. Brain corpus excluded.
+- **Live job:** [`6a91ba00984507d9db4ea07f`](https://huggingface.co/jobs/SZLHOLDINGS/6a91ba00984507d9db4ea07f) namespace `SZLHOLDINGS`. RUNNING (`UV_HTTP_TIMEOUT=300`). Train receipt absent until finish.
+- **Prior jobs (MEASURED failed, no weights):** `6a91b8ba984507d9db4ea071` CastError on mixed dataset files; `6a91b990984507d9db4ea077` uv download timeout 30s.
 ## Limitations