Instructions to use troysaved/claimtrace-smoke with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use troysaved/claimtrace-smoke with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("troysaved/claimtrace-smoke")
model = AutoModelForCausalLM.from_pretrained("troysaved/claimtrace-smoke", 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 troysaved/claimtrace-smoke with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/troysaved/claimtrace-smoke

SGLang

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

Unsloth Desktop
Docker Model Runner
How to use troysaved/claimtrace-smoke with Docker Model Runner:
```
docker model run hf.co/troysaved/claimtrace-smoke
```

troysaved commited on 9 days ago

Commit

d1c7d44

verified ·

1 Parent(s): 4fb7e97

card: mark as smoke-test artifact, point to the real submission

Browse files

Files changed (1) hide show

README.md +24 -13

README.md CHANGED Viewed

@@ -1,21 +1,32 @@
 ---
 base_model: unsloth/qwen3-1.7b-unsloth-bnb-4bit
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- qwen3
 license: apache-2.0
-language:
-- en
 ---
-# Uploaded finetuned  model
-- **Developed by:** troysaved
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/qwen3-1.7b-unsloth-bnb-4bit
-This qwen3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 ---
 base_model: unsloth/qwen3-1.7b-unsloth-bnb-4bit
+library_name: transformers
 license: apache-2.0
+language: [en]
+tags: [claimtrace, smoke-test, not-the-submission, qwen3, unsloth]
 ---
+# claimtrace — smoke-test artifact (NOT the submission)
+> **Looking for the claimtrace model? It is
+> [`troysaved/claimtrace-qwen3-1.7b`](https://huggingface.co/troysaved/claimtrace-qwen3-1.7b).**
+> This repo is not that model and should not be evaluated as it.
+This is a throwaway checkpoint from a 6-conversation end-to-end pipeline test
+(`smoke.sh`: generate → train → eval on a tiny batch), uploaded on 2026-08-19 to
+prove the publish path worked before the real run was pushed. It was trained on a
+smoke batch, not on the dataset, and it holds no meaningful behavior. Its numbers
+are not reported anywhere and it is not referenced by the submission.
+It is kept public rather than deleted so that any link created while the publish
+path was being tested still resolves to an explanation instead of a 404.
+## The actual submission
+| | |
+|---|---|
+| Model | [`troysaved/claimtrace-qwen3-1.7b`](https://huggingface.co/troysaved/claimtrace-qwen3-1.7b) @ `d02f380b37e5ce2ea8d816ff8379718148874b66` (run `qadv1`) |
+| Dataset | [`troysaved/claimtrace-ledger-dataset`](https://huggingface.co/datasets/troysaved/claimtrace-ledger-dataset) @ `9ee828685f5aba3d0f9ac4edf69a40b9b3dc82f9` (v4 spec, 407 conversations) |
+| Behavior | A tutoring model that keeps a claim-provenance ledger: an item enters `KNOWN` only after the learner demonstrates it; a self-report is `CLAIMED`, however plausible. |
+Trained with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face TRL.