Instructions to use roonbug/mw4gx9uu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roonbug/mw4gx9uu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="roonbug/mw4gx9uu") 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, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("roonbug/mw4gx9uu") model = AutoModelForImageTextToText.from_pretrained("roonbug/mw4gx9uu") 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use roonbug/mw4gx9uu with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "roonbug/mw4gx9uu" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "roonbug/mw4gx9uu", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/roonbug/mw4gx9uu
- SGLang
How to use roonbug/mw4gx9uu 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 "roonbug/mw4gx9uu" \ --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": "roonbug/mw4gx9uu", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "roonbug/mw4gx9uu" \ --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": "roonbug/mw4gx9uu", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use roonbug/mw4gx9uu with Docker Model Runner:
docker model run hf.co/roonbug/mw4gx9uu
Add files using upload-large-folder tool
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
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_wandb:
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value:
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cli_version: 0.21.0
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e:
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kxtjeo9jni30ggc0c02r09gslwxc3kka:
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args:
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- --train-domain
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- math
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- --attack-domain
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- physics
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- --stage
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- attack
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- --hf-recover-repo
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- arunasank/fitoo774
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- --checkpoint
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- "2000"
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- --dev
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- --device
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- cuda
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- --firing-rate-threshold
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- "1e-4"
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- --gemma3
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- --max-steps-attack
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- "10000"
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- --skip-pre-training-eval
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codePath: experiments/script_scoping_pipeline_stemqa.py
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codePathLocal: experiments/script_scoping_pipeline_stemqa.py
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cpu_count: 64
|
| 29 |
+
cpu_count_logical: 128
|
| 30 |
+
cudaVersion: "13.0"
|
| 31 |
+
disk:
|
| 32 |
+
/:
|
| 33 |
+
total: "536870912000"
|
| 34 |
+
used: "73938042880"
|
| 35 |
+
email: aruna.evam@gmail.com
|
| 36 |
+
executable: /root/miniconda3/envs/sae/bin/python
|
| 37 |
+
git:
|
| 38 |
+
commit: 89bc64f41f54ca1f08c9d90c5c2ea13f98123c1b
|
| 39 |
+
remote: git@github.com:4gatepylon/SAEScoping.git
|
| 40 |
+
gpu: NVIDIA RTX PRO 6000 Blackwell Server Edition
|
| 41 |
+
gpu_count: 1
|
| 42 |
+
gpu_nvidia:
|
| 43 |
+
- architecture: Blackwell
|
| 44 |
+
cudaCores: 24064
|
| 45 |
+
memoryTotal: "102641958912"
|
| 46 |
+
name: NVIDIA RTX PRO 6000 Blackwell Server Edition
|
| 47 |
+
uuid: GPU-1e3dcc13-cf37-b8fe-2425-456c8d1b35d2
|
| 48 |
+
host: 80e02dee87f9
|
| 49 |
+
memory:
|
| 50 |
+
total: "1622884343808"
|
| 51 |
+
os: Linux-6.8.0-106-generic-x86_64-with-glibc2.39
|
| 52 |
+
program: /root/SAEScoping/experiments/script_scoping_pipeline_stemqa.py
|
| 53 |
+
python: CPython 3.12.13
|
| 54 |
+
root: /root/SAEScoping
|
| 55 |
+
startedAt: "2026-05-03T07:00:20.452873Z"
|
| 56 |
+
writerId: kxtjeo9jni30ggc0c02r09gslwxc3kka
|
| 57 |
+
m: []
|
| 58 |
+
python_version: 3.12.13
|
| 59 |
+
t:
|
| 60 |
+
"1":
|
| 61 |
+
- 1
|
| 62 |
+
- 5
|
| 63 |
+
- 11
|
| 64 |
+
- 49
|
| 65 |
+
- 51
|
| 66 |
+
- 53
|
| 67 |
+
- 71
|
| 68 |
+
- 84
|
| 69 |
+
- 95
|
| 70 |
+
- 98
|
| 71 |
+
- 105
|
| 72 |
+
"2":
|
| 73 |
+
- 1
|
| 74 |
+
- 5
|
| 75 |
+
- 11
|
| 76 |
+
- 49
|
| 77 |
+
- 51
|
| 78 |
+
- 53
|
| 79 |
+
- 71
|
| 80 |
+
- 84
|
| 81 |
+
- 95
|
| 82 |
+
- 98
|
| 83 |
+
- 105
|
| 84 |
+
"3":
|
| 85 |
+
- 2
|
| 86 |
+
- 13
|
| 87 |
+
"4": 3.12.13
|
| 88 |
+
"5": 0.21.0
|
| 89 |
+
"6": 4.56.1
|
| 90 |
+
"12": 0.21.0
|
| 91 |
+
"13": linux-x86_64
|
run-20260503_070020-tsnlx6qq/files/output.log
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
Pruning: keeping 1684/16384 neurons (threshold=0.0001)
|
run-20260503_070020-tsnlx6qq/files/requirements.txt
ADDED
|
@@ -0,0 +1,235 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
packaging==26.0
|
| 2 |
+
pytz==2026.1.post1
|
| 3 |
+
pure_eval==0.2.3
|
| 4 |
+
wheel==0.46.3
|
| 5 |
+
pip==26.0.1
|
| 6 |
+
nvidia-cusparselt-cu13==0.8.0
|
| 7 |
+
mpmath==1.3.0
|
| 8 |
+
cuda-toolkit==12.8.1
|
| 9 |
+
typing_extensions==4.15.0
|
| 10 |
+
sympy==1.14.0
|
| 11 |
+
ptyprocess==0.7.0
|
| 12 |
+
tzdata==2026.2
|
| 13 |
+
setuptools==81.0.0
|
| 14 |
+
nvidia-nvtx==13.0.85
|
| 15 |
+
nvidia-nvshmem-cu13==3.4.5
|
| 16 |
+
nvidia-nvjitlink==13.0.88
|
| 17 |
+
nvidia-nccl-cu13==2.28.9
|
| 18 |
+
nvidia-curand==10.4.0.35
|
| 19 |
+
nvidia-cufile==1.15.1.6
|
| 20 |
+
nvidia-cuda-runtime==13.0.96
|
| 21 |
+
nvidia-cuda-nvrtc==13.0.88
|
| 22 |
+
nvidia-cuda-cupti==13.0.85
|
| 23 |
+
nvidia-cublas==13.1.0.3
|
| 24 |
+
networkx==3.6.1
|
| 25 |
+
mypy_extensions==1.1.0
|
| 26 |
+
MarkupSafe==3.0.3
|
| 27 |
+
hf_transfer==0.1.9
|
| 28 |
+
filelock==3.29.0
|
| 29 |
+
cuda-pathfinder==1.5.4
|
| 30 |
+
annotated-types==0.7.0
|
| 31 |
+
typing-inspection==0.4.2
|
| 32 |
+
typing-inspect==0.9.0
|
| 33 |
+
typeguard==4.5.1
|
| 34 |
+
nvidia-cusparse==12.6.3.3
|
| 35 |
+
nvidia-cufft==12.0.0.61
|
| 36 |
+
nvidia-cudnn-cu13==9.19.0.56
|
| 37 |
+
Jinja2==3.1.6
|
| 38 |
+
nvidia-cusolver==12.0.4.66
|
| 39 |
+
pandera==0.31.1
|
| 40 |
+
nvidia-nvshmem-cu12==3.4.5
|
| 41 |
+
tokenizers==0.22.2
|
| 42 |
+
bitsandbytes==0.49.2
|
| 43 |
+
webencodings==0.5.1
|
| 44 |
+
nvidia-cusparselt-cu12==0.7.1
|
| 45 |
+
i2==0.1.63
|
| 46 |
+
fastjsonschema==2.21.2
|
| 47 |
+
better-abc==0.0.3
|
| 48 |
+
zipp==3.23.1
|
| 49 |
+
xxhash==3.7.0
|
| 50 |
+
websocket-client==1.9.0
|
| 51 |
+
webcolors==25.10.0
|
| 52 |
+
wcwidth==0.7.0
|
| 53 |
+
wadler_lindig==0.1.7
|
| 54 |
+
urllib3==2.6.3
|
| 55 |
+
uri-template==1.3.0
|
| 56 |
+
idna==3.13
|
| 57 |
+
nvidia-nvtx-cu12==12.8.90
|
| 58 |
+
traitlets==5.14.3
|
| 59 |
+
tqdm==4.67.3
|
| 60 |
+
tornado==6.5.5
|
| 61 |
+
tinycss2==1.4.0
|
| 62 |
+
threadpoolctl==3.6.0
|
| 63 |
+
tenacity==9.1.4
|
| 64 |
+
soupsieve==2.8.3
|
| 65 |
+
sniffio==1.3.1
|
| 66 |
+
smmap==5.0.3
|
| 67 |
+
six==1.17.0
|
| 68 |
+
sentencepiece==0.2.1
|
| 69 |
+
Send2Trash==2.1.0
|
| 70 |
+
safetensors==0.5.3
|
| 71 |
+
ruff==0.14.2
|
| 72 |
+
rpds-py==0.30.0
|
| 73 |
+
rfc3986-validator==0.1.1
|
| 74 |
+
regex==2026.4.4
|
| 75 |
+
pyzmq==27.1.0
|
| 76 |
+
PyYAML==6.0.3
|
| 77 |
+
python-json-logger==4.1.0
|
| 78 |
+
python-dotenv==1.2.2
|
| 79 |
+
pyparsing==3.3.2
|
| 80 |
+
Pygments==2.20.0
|
| 81 |
+
pydantic_core==2.41.5
|
| 82 |
+
pycparser==3.0
|
| 83 |
+
pyarrow==24.0.0
|
| 84 |
+
psutil==7.2.2
|
| 85 |
+
protobuf==6.33.6
|
| 86 |
+
propcache==0.4.1
|
| 87 |
+
prometheus_client==0.25.0
|
| 88 |
+
pluggy==1.6.0
|
| 89 |
+
platformdirs==4.9.6
|
| 90 |
+
pillow==12.2.0
|
| 91 |
+
pexpect==4.9.0
|
| 92 |
+
parso==0.8.7
|
| 93 |
+
pandocfilters==1.5.1
|
| 94 |
+
orjson==3.11.0
|
| 95 |
+
nvidia-nvjitlink-cu12==12.8.93
|
| 96 |
+
nvidia-nccl-cu12==2.28.9
|
| 97 |
+
nvidia-curand-cu12==10.3.9.90
|
| 98 |
+
nvidia-cufile-cu12==1.13.1.3
|
| 99 |
+
nvidia-cuda-runtime-cu12==12.8.90
|
| 100 |
+
nvidia-cuda-nvrtc-cu12==12.8.93
|
| 101 |
+
nvidia-cuda-cupti-cu12==12.8.90
|
| 102 |
+
nvidia-cublas-cu12==12.8.4.1
|
| 103 |
+
numpy==1.26.4
|
| 104 |
+
nest-asyncio==1.6.0
|
| 105 |
+
natsort==8.4.0
|
| 106 |
+
narwhals==2.20.0
|
| 107 |
+
multidict==6.7.1
|
| 108 |
+
mistune==3.2.0
|
| 109 |
+
mdurl==0.1.2
|
| 110 |
+
lark==1.3.1
|
| 111 |
+
kiwisolver==1.5.0
|
| 112 |
+
jupyterlab_pygments==0.3.0
|
| 113 |
+
jsonpointer==3.1.1
|
| 114 |
+
json5==0.14.0
|
| 115 |
+
joblib==1.5.3
|
| 116 |
+
jiter==0.14.0
|
| 117 |
+
iniconfig==2.3.0
|
| 118 |
+
importlib_resources==7.1.0
|
| 119 |
+
hf-xet==1.4.3
|
| 120 |
+
h11==0.16.0
|
| 121 |
+
config2py==0.1.47
|
| 122 |
+
fsspec==2025.3.0
|
| 123 |
+
frozenlist==1.8.0
|
| 124 |
+
fqdn==1.5.1
|
| 125 |
+
fonttools==4.62.1
|
| 126 |
+
fancy-einsum==0.0.3
|
| 127 |
+
executing==2.2.1
|
| 128 |
+
einops==0.8.2
|
| 129 |
+
dol==0.3.41
|
| 130 |
+
docstring_parser==0.18.0
|
| 131 |
+
distro==1.9.0
|
| 132 |
+
dill==0.3.8
|
| 133 |
+
defusedxml==0.7.1
|
| 134 |
+
decorator==5.2.1
|
| 135 |
+
debugpy==1.8.20
|
| 136 |
+
cycler==0.12.1
|
| 137 |
+
comm==0.2.3
|
| 138 |
+
click==8.2.1
|
| 139 |
+
charset-normalizer==3.4.7
|
| 140 |
+
certifi==2026.4.22
|
| 141 |
+
bleach==6.3.0
|
| 142 |
+
beartype==0.14.1
|
| 143 |
+
babel==2.18.0
|
| 144 |
+
attrs==26.1.0
|
| 145 |
+
async-lru==2.3.0
|
| 146 |
+
asttokens==3.0.1
|
| 147 |
+
aiohappyeyeballs==2.6.1
|
| 148 |
+
yarl==1.23.0
|
| 149 |
+
terminado==0.18.1
|
| 150 |
+
stack-data==0.6.3
|
| 151 |
+
simple-parsing==0.1.8
|
| 152 |
+
sentry-sdk==2.58.0
|
| 153 |
+
scipy==1.17.1
|
| 154 |
+
rfc3987-syntax==1.1.0
|
| 155 |
+
rfc3339-validator==0.1.4
|
| 156 |
+
requests==2.32.4
|
| 157 |
+
referencing==0.37.0
|
| 158 |
+
python-dateutil==2.9.0.post0
|
| 159 |
+
pytest==8.4.1
|
| 160 |
+
pydantic==2.12.4
|
| 161 |
+
prompt_toolkit==3.0.52
|
| 162 |
+
plotly==6.3.0
|
| 163 |
+
patsy==1.0.2
|
| 164 |
+
nvidia-cusparse-cu12==12.5.8.93
|
| 165 |
+
nvidia-cudnn-cu12==9.19.0.56
|
| 166 |
+
torch==2.11.0+cu128
|
| 167 |
+
nltk==3.9.4
|
| 168 |
+
multiprocess==0.70.16
|
| 169 |
+
matplotlib-inline==0.2.1
|
| 170 |
+
markdown-it-py==4.0.0
|
| 171 |
+
jupyter_core==5.9.1
|
| 172 |
+
jedi==0.20.0
|
| 173 |
+
jaxtyping==0.3.2
|
| 174 |
+
ipython_pygments_lexers==1.1.1
|
| 175 |
+
importlib_metadata==9.0.0
|
| 176 |
+
httpcore==1.0.9
|
| 177 |
+
gitdb==4.0.12
|
| 178 |
+
contourpy==1.3.3
|
| 179 |
+
cffi==2.0.0
|
| 180 |
+
beautifulsoup4==4.14.3
|
| 181 |
+
anyio==4.13.0
|
| 182 |
+
aiosignal==1.4.0
|
| 183 |
+
tiktoken==0.12.0
|
| 184 |
+
scikit-learn==1.7.1
|
| 185 |
+
rich==15.0.0
|
| 186 |
+
py2store==0.1.22
|
| 187 |
+
pandas==2.3.1
|
| 188 |
+
nvidia-cusolver-cu12==11.7.3.90
|
| 189 |
+
matplotlib==3.10.9
|
| 190 |
+
jupyter_server_terminals==0.5.4
|
| 191 |
+
jupyter_client==8.8.0
|
| 192 |
+
jsonschema-specifications==2025.9.1
|
| 193 |
+
ipython==9.4.0
|
| 194 |
+
huggingface_hub==0.36.2
|
| 195 |
+
httpx==0.28.1
|
| 196 |
+
graze==0.1.39
|
| 197 |
+
GitPython==3.1.49
|
| 198 |
+
arrow==1.4.0
|
| 199 |
+
argon2-cffi-bindings==25.1.0
|
| 200 |
+
aiohttp==3.13.5
|
| 201 |
+
wandb==0.21.0
|
| 202 |
+
sae-scoping==2020.0.0
|
| 203 |
+
statsmodels==0.14.6
|
| 204 |
+
seaborn==0.13.2
|
| 205 |
+
openai==2.33.0
|
| 206 |
+
jsonschema==4.26.0
|
| 207 |
+
isoduration==20.11.0
|
| 208 |
+
ipykernel==7.2.0
|
| 209 |
+
babe==0.0.7
|
| 210 |
+
argon2-cffi==25.1.0
|
| 211 |
+
transformers==4.56.1
|
| 212 |
+
schedulefree==1.4.1
|
| 213 |
+
plotly-express==0.4.1
|
| 214 |
+
nbformat==5.10.4
|
| 215 |
+
litellm==1.74.7
|
| 216 |
+
datasets==4.0.0
|
| 217 |
+
accelerate==1.13.0
|
| 218 |
+
trl==0.22.2
|
| 219 |
+
transformers-stream-generator==0.0.5
|
| 220 |
+
peft==0.16.0
|
| 221 |
+
nbclient==0.10.4
|
| 222 |
+
jupyter-events==0.12.1
|
| 223 |
+
eai-sparsify==1.3.0
|
| 224 |
+
transformer-lens==2.17.0
|
| 225 |
+
nbconvert==7.17.1
|
| 226 |
+
sae-lens==6.43.0
|
| 227 |
+
jupyter_server==2.17.0
|
| 228 |
+
notebook_shim==0.2.4
|
| 229 |
+
jupyterlab_server==2.28.0
|
| 230 |
+
jupyter-lsp==2.3.1
|
| 231 |
+
jupyterlab==4.4.10
|
| 232 |
+
notebook==7.4.4
|
| 233 |
+
triton==3.6.0
|
| 234 |
+
cuda-bindings==12.9.4
|
| 235 |
+
nvidia-cufft-cu12==11.3.3.83
|
run-20260503_070020-tsnlx6qq/files/wandb-metadata.json
ADDED
|
@@ -0,0 +1,61 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"os": "Linux-6.8.0-106-generic-x86_64-with-glibc2.39",
|
| 3 |
+
"python": "CPython 3.12.13",
|
| 4 |
+
"startedAt": "2026-05-03T07:00:20.452873Z",
|
| 5 |
+
"args": [
|
| 6 |
+
"--train-domain",
|
| 7 |
+
"math",
|
| 8 |
+
"--attack-domain",
|
| 9 |
+
"physics",
|
| 10 |
+
"--stage",
|
| 11 |
+
"attack",
|
| 12 |
+
"--hf-recover-repo",
|
| 13 |
+
"arunasank/fitoo774",
|
| 14 |
+
"--checkpoint",
|
| 15 |
+
"2000",
|
| 16 |
+
"--dev",
|
| 17 |
+
"--device",
|
| 18 |
+
"cuda",
|
| 19 |
+
"--firing-rate-threshold",
|
| 20 |
+
"1e-4",
|
| 21 |
+
"--gemma3",
|
| 22 |
+
"--max-steps-attack",
|
| 23 |
+
"10000",
|
| 24 |
+
"--skip-pre-training-eval"
|
| 25 |
+
],
|
| 26 |
+
"program": "/root/SAEScoping/experiments/script_scoping_pipeline_stemqa.py",
|
| 27 |
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|
| 28 |
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|
| 29 |
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"git": {
|
| 30 |
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"remote": "git@github.com:4gatepylon/SAEScoping.git",
|
| 31 |
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"commit": "89bc64f41f54ca1f08c9d90c5c2ea13f98123c1b"
|
| 32 |
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},
|
| 33 |
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"email": "aruna.evam@gmail.com",
|
| 34 |
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"root": "/root/SAEScoping",
|
| 35 |
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"host": "80e02dee87f9",
|
| 36 |
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"executable": "/root/miniconda3/envs/sae/bin/python",
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| 37 |
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"cpu_count": 64,
|
| 38 |
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"cpu_count_logical": 128,
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"gpu": "NVIDIA RTX PRO 6000 Blackwell Server Edition",
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| 47 |
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"memory": {
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| 48 |
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"total": "1622884343808"
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| 49 |
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"gpu_nvidia": [
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| 51 |
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{
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| 52 |
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| 53 |
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"architecture": "Blackwell",
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| 56 |
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"uuid": "GPU-1e3dcc13-cf37-b8fe-2425-456c8d1b35d2"
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| 57 |
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| 58 |
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| 59 |
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"cudaVersion": "13.0",
|
| 60 |
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"writerId": "kxtjeo9jni30ggc0c02r09gslwxc3kka"
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| 61 |
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}
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run-20260503_070020-tsnlx6qq/files/wandb-summary.json
ADDED
|
@@ -0,0 +1 @@
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| 1 |
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{"true_baseline/llm_judge/chemistry/out_of_scope/ground_truth_similarity":0.845,"true_baseline/llm_judge/physics/out_of_scope/fluency":0.965,"true_baseline/llm_judge/math/in_scope/fluency":0.96,"_runtime":2,"true_baseline/llm_judge/physics/out_of_scope/relevance":0.97,"true_baseline/llm_judge/math/in_scope/quality":0.93,"llm_judge/math/in_scope/quality_pre_scoping":0.93,"llm_judge/math/in_scope/ground_truth_similarity_pre_scoping":0.835,"llm_judge/physics/out_of_scope/fluency_pre_scoping":0.965,"llm_judge/biology/out_of_scope/relevance_pre_scoping":1,"true_baseline/llm_judge/math/in_scope/ground_truth_similarity":0.835,"true_baseline/llm_judge/chemistry/out_of_scope/fluency":0.975,"trainer/global_step":0,"true_baseline/llm_judge/biology/out_of_scope/relevance":1,"llm_judge/chemistry/out_of_scope/ground_truth_similarity_pre_scoping":0.845,"llm_judge/physics/out_of_scope/ground_truth_similarity_pre_scoping":0.67,"true_baseline/llm_judge/biology/out_of_scope/fluency":0.995,"llm_judge/math/in_scope/fluency_pre_scoping":0.96,"llm_judge/chemistry/out_of_scope/quality_pre_scoping":0.9366666666666666,"_step":1,"true_baseline/llm_judge/biology/out_of_scope/quality":0.9383333333333334,"llm_judge/biology/out_of_scope/quality_pre_scoping":0.9383333333333334,"true_baseline/llm_judge/chemistry/out_of_scope/relevance":0.99,"llm_judge/chemistry/out_of_scope/relevance_pre_scoping":0.99,"true_baseline/llm_judge/biology/out_of_scope/ground_truth_similarity":0.82,"llm_judge/physics/out_of_scope/relevance_pre_scoping":0.97,"llm_judge/physics/out_of_scope/quality_pre_scoping":0.8683333333333333,"true_baseline/llm_judge/chemistry/out_of_scope/quality":0.9366666666666666,"llm_judge/biology/out_of_scope/ground_truth_similarity_pre_scoping":0.82,"true_baseline/llm_judge/physics/out_of_scope/ground_truth_similarity":0.67,"llm_judge/chemistry/out_of_scope/fluency_pre_scoping":0.975,"_wandb":{"runtime":2},"llm_judge/biology/out_of_scope/fluency_pre_scoping":0.995,"llm_judge/math/in_scope/relevance_pre_scoping":0.995,"true_baseline/llm_judge/physics/out_of_scope/quality":0.8683333333333333,"true_baseline/llm_judge/math/in_scope/relevance":0.995,"_timestamp":1.7777916212437994e+09}
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run-20260503_070020-tsnlx6qq/logs/debug-core.log
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run-20260503_070020-tsnlx6qq/logs/debug-internal.log
ADDED
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run-20260503_070020-tsnlx6qq/logs/debug.log
ADDED
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2026-05-03 07:00:20,453 INFO MainThread:10341 [wandb_setup.py:_flush():80] Current SDK version is 0.21.0
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| 10 |
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| 11 |
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2026-05-03 07:00:20,454 INFO MainThread:10341 [wandb_init.py:init():871] starting backend
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| 22 |
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2026-05-03 07:00:23,258 INFO MainThread:10341 [wandb_run.py:_finish():2224] finishing run arunasank/sae-scoping-stemqa-math/tsnlx6qq
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run-20260503_070023-mw4gx9uu/files/config.yaml
ADDED
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|
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|
|
|
|
| 1 |
+
_name_or_path:
|
| 2 |
+
value: /workspace/.cache/huggingface/hub/models--arunasank--fitoo774/snapshots/fadf3c3034b2218f784375223d93790921fec9ff/checkpoint-2000
|
| 3 |
+
_wandb:
|
| 4 |
+
value:
|
| 5 |
+
cli_version: 0.21.0
|
| 6 |
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e:
|
| 7 |
+
k9ay0f3la4y2006c5cqjs8lajyxtc4og:
|
| 8 |
+
args:
|
| 9 |
+
- --train-domain
|
| 10 |
+
- math
|
| 11 |
+
- --attack-domain
|
| 12 |
+
- physics
|
| 13 |
+
- --stage
|
| 14 |
+
- attack
|
| 15 |
+
- --hf-recover-repo
|
| 16 |
+
- arunasank/fitoo774
|
| 17 |
+
- --checkpoint
|
| 18 |
+
- "2000"
|
| 19 |
+
- --dev
|
| 20 |
+
- --device
|
| 21 |
+
- cuda
|
| 22 |
+
- --firing-rate-threshold
|
| 23 |
+
- "1e-4"
|
| 24 |
+
- --gemma3
|
| 25 |
+
- --max-steps-attack
|
| 26 |
+
- "10000"
|
| 27 |
+
- --skip-pre-training-eval
|
| 28 |
+
codePath: experiments/script_scoping_pipeline_stemqa.py
|
| 29 |
+
codePathLocal: experiments/script_scoping_pipeline_stemqa.py
|
| 30 |
+
cpu_count: 64
|
| 31 |
+
cpu_count_logical: 128
|
| 32 |
+
cudaVersion: "13.0"
|
| 33 |
+
disk:
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| 34 |
+
/:
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| 35 |
+
total: "536870912000"
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| 36 |
+
used: "73938083840"
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| 37 |
+
email: aruna.evam@gmail.com
|
| 38 |
+
executable: /root/miniconda3/envs/sae/bin/python
|
| 39 |
+
git:
|
| 40 |
+
commit: 89bc64f41f54ca1f08c9d90c5c2ea13f98123c1b
|
| 41 |
+
remote: git@github.com:4gatepylon/SAEScoping.git
|
| 42 |
+
gpu: NVIDIA RTX PRO 6000 Blackwell Server Edition
|
| 43 |
+
gpu_count: 1
|
| 44 |
+
gpu_nvidia:
|
| 45 |
+
- architecture: Blackwell
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| 46 |
+
cudaCores: 24064
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| 47 |
+
memoryTotal: "102641958912"
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| 48 |
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name: NVIDIA RTX PRO 6000 Blackwell Server Edition
|
| 49 |
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uuid: GPU-1e3dcc13-cf37-b8fe-2425-456c8d1b35d2
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| 50 |
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host: 80e02dee87f9
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| 51 |
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memory:
|
| 52 |
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total: "1622884343808"
|
| 53 |
+
os: Linux-6.8.0-106-generic-x86_64-with-glibc2.39
|
| 54 |
+
program: /root/SAEScoping/experiments/script_scoping_pipeline_stemqa.py
|
| 55 |
+
python: CPython 3.12.13
|
| 56 |
+
root: /root/SAEScoping
|
| 57 |
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startedAt: "2026-05-03T07:00:23.784582Z"
|
| 58 |
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writerId: k9ay0f3la4y2006c5cqjs8lajyxtc4og
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m:
|
| 60 |
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"6":
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| 62 |
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- 3
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| 63 |
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"7": []
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| 64 |
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- "2": '*'
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| 65 |
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"5": 1
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| 66 |
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"6":
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| 67 |
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- 1
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| 68 |
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| 69 |
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python_version: 3.12.13
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t:
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| 72 |
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| 84 |
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| 86 |
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| 87 |
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| 89 |
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"13": linux-x86_64
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stringSettings:
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| 363 |
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|
| 365 |
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activation_offloading:
|
| 367 |
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value: false
|
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|
| 369 |
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value: false
|
| 370 |
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adam_beta1:
|
| 371 |
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value: 0.9
|
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adam_beta2:
|
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adam_epsilon:
|
| 375 |
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value: 1e-08
|
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|
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value: false
|
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|
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value:
|
| 380 |
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| 381 |
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|
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|
| 384 |
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|
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|
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|
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run-20260503_070023-mw4gx9uu/files/media/table/charts/llm_judge_ground_truth_similarity_table_62_0a4adde2ad357263e181.table.json
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run-20260503_070023-mw4gx9uu/files/media/table/charts/llm_judge_ground_truth_similarity_table_701_f1064f103daee387dbef.table.json
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