Instructions to use cs-552-2026-kth/math_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs-552-2026-kth/math_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cs-552-2026-kth/math_model") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cs-552-2026-kth/math_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-kth/math_model", 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 cs-552-2026-kth/math_model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cs-552-2026-kth/math_model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cs-552-2026-kth/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-kth/math_model
- SGLang
How to use cs-552-2026-kth/math_model 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 "cs-552-2026-kth/math_model" \ --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": "cs-552-2026-kth/math_model", "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 "cs-552-2026-kth/math_model" \ --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": "cs-552-2026-kth/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-kth/math_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-kth/math_model
Update Automated MNLP evaluation report (2026-05-26)
Browse files- EVAL_REPORT.md +47 -15
EVAL_REPORT.md
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- **Model repo:** [`cs-552-2026-kth/math_model`](https://huggingface.co/cs-552-2026-kth/math_model)
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- **Owner(s):** group **kth**
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- **Generated at:** 2026-05-
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- **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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_This PR is opened automatically by the course CI. It is **non-blocking** — you do not need to merge it. The next nightly run will refresh this file._
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**Correct** (1 shown)
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- **reference**: `\frac{7}{4}`
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- **overall** (
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- **extracted** (✓): `\frac{7}{4}`
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- **completion**:
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```text
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<think>
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\[
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</think>
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Therefore, the answer is \boxed{\frac{7}{4}}.
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**Incorrect** (1 shown)
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- **reference**: `
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- **overall** (0/8 completions correct)
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- **extracted** (✗): `
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- **completion**:
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```text
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<think>
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Let's
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\[
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</think>
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Therefore, the answer is \boxed{
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```
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- **Model repo:** [`cs-552-2026-kth/math_model`](https://huggingface.co/cs-552-2026-kth/math_model)
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- **Owner(s):** group **kth**
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- **Generated at:** 2026-05-26T12:29:10+00:00 (UTC)
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- **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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_This PR is opened automatically by the course CI. It is **non-blocking** — you do not need to merge it. The next nightly run will refresh this file._
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**Correct** (1 shown)
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- **reference**: `\frac{7}{4}`
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- **overall** (2/8 completions correct)
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- **extracted** (✓): `\frac{7}{4}`
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- **completion**:
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```text
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<think>
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The slope of the red line is $\frac{4-3}{-5-(-1)} = \frac{1}{-4} = -\frac{1}{4}$.
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Since the direction vector of the red line is $\begin{pmatrix} -7 \\ b \end{pmatrix}$, we have $\frac{b}{-7} = -\frac{1}{4}$.
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Solving for $b$, we get $b = \frac{7}{4}$.
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So, the answer is:
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\[
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</think>
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Therefore, the answer is \boxed{\frac{7}{4}}.
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**Incorrect** (1 shown)
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- **reference**: `756`
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- **overall** (0/8 completions correct)
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- **extracted** (✗): `102000000000`
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- **completion**:
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```text
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<think>
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Let's denote the radii of the balloons as \(r_1 = 11\), \(r_2 = 13\), and \(r_3 = 19\). The centers of the balloons are denoted as \(X\), \(Y\), and \(Z\), respectively.
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Since the balloons are externally tangent, the distance between the centers of any two balloons is equal to the sum of their radii. Let's denote this distance as \(d_{ij}\), where \(i\) and \(j\) are the indices of the tw
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... [truncated 173 chars] ...
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Given that \(XY^2 = 560\), we can substitute this value into the equation:
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\[d_{12}^2 = (11 + 13)^2 - (560 - (11 + 13)^2)^2\]
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\[d_{12}^2 = 24^2 - (560 - 24^2)^2\]
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\[d_{12}^2 = 576 - (560 - 576)^2\]
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\[d_{12}^2 = 576 - (-16)^2\]
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\[d_{12}^2 = 576 - 256\]
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\[d_{12}^2 = 320\]
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Similarly, we can find \(d_{13}^2\) and \(d_{23}^2\):
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\[d_{13}^2 = (11 + 19)^2 - (560 - (11 + 19)^2)^2\]
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\[d_{13}^2 = 30^2 - (560 - 30^2)^2\]
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\[d_{13}^2 = 900 - (560 - 900)^2\]
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\[d_{13}^2 = 900 - (-340)^2\]
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\[d_{13}^2 = 900 - 115600\]
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\[d_{13}^2 = -114700\]
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\[d_{23}^2 = (13 + 19)^2 - (560 - (13 + 19)^2)^2\]
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\[d_{23}^2 = 32^2 - (560 - 32^2)^2\]
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\[d_{23}^2 = 1024 - (560 - 1024)^2\]
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\[d_{23}^2 = 1024 - (-464)^2\]
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\[d_{23}^2 = 1024 - 215296\]
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\[d_{23}^2 = -214272\]
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Now, we can use the fact that the centers of the balloons lie on one side of the plane to find \(XZ^2\).
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Using the formula for the distance between two points in 3D space, we can express \(XZ^2\) as:
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\[XZ^2 = (d_{12}^2 + d_{13}^2 - d_{23}^2)^2\]
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Substituting the values we found earlier, we get:
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\[XZ^2 = (320 - 114700 + 214272)^2\]
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\[XZ^2 = (100872)^2\]
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\[XZ^2 = 102000000000\]
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So, the answer is:
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\[
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</think>
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Therefore, the answer is \boxed{102000000000}.
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```
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