Instructions to use jerryyan/TraceML-Action-Labeler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jerryyan/TraceML-Action-Labeler with Transformers:

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

pipe = pipeline("text-generation", model="jerryyan/TraceML-Action-Labeler")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jerryyan/TraceML-Action-Labeler")
model = AutoModelForCausalLM.from_pretrained("jerryyan/TraceML-Action-Labeler", 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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

ml-agents

How to use jerryyan/TraceML-Action-Labeler with ml-agents:

mlagents-load-from-hf --repo-id="jerryyan/TraceML-Action-Labeler" --local-dir="./downloads"

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jerryyan/TraceML-Action-Labeler with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/jerryyan/TraceML-Action-Labeler

SGLang

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

Docker Model Runner
How to use jerryyan/TraceML-Action-Labeler with Docker Model Runner:
```
docker model run hf.co/jerryyan/TraceML-Action-Labeler
```

jerryyan commited on Sep 28

Commit

d5ad65d

verified ·

1 Parent(s): ab1f5d0

Card: new paper title and NeurIPS 2026 citation

Browse files

Files changed (1) hide show

README.md +9 -5

README.md CHANGED Viewed

@@ -17,6 +17,8 @@ tags:
 # TraceML Action Labeler (Qwen3-1.7B)
 [📄 Paper](https://arxiv.org/abs/2608.26086) · [🤗 Dataset](https://huggingface.co/datasets/jerryyan/TraceML) · [💻 Toolkit](https://github.com/JerryYan123/TraceML) · [🌐 Project page](https://jerryyan123.github.io/TraceML/) · [State labeler](https://huggingface.co/jerryyan/TraceML-State-Labeler)
 The action labeler of [TraceML](https://jerryyan123.github.io/TraceML/) (NeurIPS 2026, Evaluations & Datasets Track). Given a transition between two versions of an ML solution (the code diff, the state labels of both versions and the score change), it returns as JSON what the edit did and why: 10 coarse actions, fine actions from a closed list of 85, one or two intents out of 6, the edit magnitude, the score effect, and short natural-language summaries.
@@ -65,10 +67,12 @@ Apache-2.0, inherited from Qwen3.
 ## Citation
 ```bibtex
-@article{yan2026traceml,
-  title   = {TraceML: An Empirical Analysis of Human-Agent Planning in Machine Learning Development},
-  author  = {Yan, Jiarui and Sun, Weiwei and Li, Sijie and Li, Wenhan and Yang, Yiming},
-  journal = {arXiv preprint arXiv:2608.26086},
-  year    = {2026}
 }
 ```

 # TraceML Action Labeler (Qwen3-1.7B)
+> **Moved:** both labelers now live in one repo, [jerryyan/TraceML-Labelers](https://huggingface.co/jerryyan/TraceML-Labelers) (`state/` and `action/`). This repo is kept only so existing links keep working.
 [📄 Paper](https://arxiv.org/abs/2608.26086) · [🤗 Dataset](https://huggingface.co/datasets/jerryyan/TraceML) · [💻 Toolkit](https://github.com/JerryYan123/TraceML) · [🌐 Project page](https://jerryyan123.github.io/TraceML/) · [State labeler](https://huggingface.co/jerryyan/TraceML-State-Labeler)
 The action labeler of [TraceML](https://jerryyan123.github.io/TraceML/) (NeurIPS 2026, Evaluations & Datasets Track). Given a transition between two versions of an ML solution (the code diff, the state labels of both versions and the score change), it returns as JSON what the edit did and why: 10 coarse actions, fine actions from a closed list of 85, one or two intents out of 6, the edit magnitude, the score effect, and short natural-language summaries.
 ## Citation
 ```bibtex
+@inproceedings{yan2026traceml,
+  title         = {TraceML: What Auto-Research Agents Miss in Long-Horizon ML Development},
+  author        = {Yan, Jiarui and Sun, Weiwei and Li, Sijie and Li, Wenhan and Yang, Yiming},
+  booktitle     = {Advances in Neural Information Processing Systems (NeurIPS), Track on Evaluations and Datasets},
+  year          = {2026},
+  eprint        = {2608.26086},
+  archivePrefix = {arXiv}
 }
 ```