Instructions to use cs-552-2026-4neurons/math_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs-552-2026-4neurons/math_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cs-552-2026-4neurons/math_model") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cs-552-2026-4neurons/math_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-4neurons/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-552-2026-4neurons/math_model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cs-552-2026-4neurons/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-552-2026-4neurons/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-4neurons/math_model
- SGLang
How to use cs-552-2026-4neurons/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-552-2026-4neurons/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-552-2026-4neurons/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-552-2026-4neurons/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-552-2026-4neurons/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-4neurons/math_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-4neurons/math_model
Automated MNLP evaluation report (2026-05-27)
#2
by zechen-nlp - opened
- EVAL_REPORT.md +18 -46
EVAL_REPORT.md
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- **Model repo:** [`cs-552-2026-4neurons/math_model`](https://huggingface.co/cs-552-2026-4neurons/math_model)
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- **Owner(s):** group **4neurons**
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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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| Benchmark | Accuracy | Status |
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| Math | 0.
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| Knowledge | — | not run |
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| Multilingual | — | not run |
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| Safety | — | not run |
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**Correct** (1 shown)
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- **reference**: `
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- **overall** (
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- **extracted** (✓): `
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- **completion**:
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```text
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<think>
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To solve for x in the equation 10^x − 10 = 9990, we need to isolate the term 10^x.
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\[ 10^x = 9990 + 10 \Rightarrow 10^x = 10000 \]
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Now, we can take the logarithm of both sides to solve for x. Since the base of the exponential term is 10, we can use the logarithm base 10.
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\[ \log_{10} 10^x = \log_{10} 10000 \Rightarrow x \log_{10} 10 = \log_{10} 10000 \]
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\[ x = \log_{10} 10000 \]
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\[ x = \log_{10} 10000 \approx 4 \]
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\[ \boxed{4} \]
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</think>
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Therefore, the
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```
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- **reference**: `
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- **overall** (0/8 completions correct)
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- **completion**:
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```text
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<think>
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The problem is asking for the probability that Derek eventually becomes debt-free, which means he never has a nonnegative debt after any number of days.
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Let's analyze the problem step-by-step:
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1. Derek starts with a debt of $\pi$ MIT.
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2. Each day, he tosses a fair coin:
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3. If his debt becomes nonpositive at any point, he is considered debt-free.
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4. If his debt is still positive after the payment, it is doubled.
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Let $P(x)$ be the probability that Derek becomes debt-free starting with a debt of $x$ MIT.
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We can write the recurrence relation as:
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\[ P(x) = \frac{1}{2} P(x - 1) + \frac{1}{2} P(x - 2) \]
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\[ P(0) = 1 \quad \text{(if his debt is 0, he is debt-free)} \]
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\[ P(x) = 0 \quad \text{if } x < 0 \quad \text{(if his debt is negative, he is debt-free)} \]
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\[ P(\pi) = \boxed{1} \]
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</think>
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```
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- **Model repo:** [`cs-552-2026-4neurons/math_model`](https://huggingface.co/cs-552-2026-4neurons/math_model)
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- **Owner(s):** group **4neurons**
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- **Generated at:** 2026-05-27T13:02:22+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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| Benchmark | Accuracy | Status |
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| Math | 0.2700 | ok |
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| Knowledge | — | not run |
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| Multilingual | — | not run |
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| Safety | — | not run |
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**Correct** (1 shown)
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- **reference**: `305`
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- **overall** (1/8 completions correct)
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- **extracted** (✓): `305`
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- **completion**:
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```text
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<think>
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</think>
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Suppose $n$ is odd. Then the pairs are $(1,2), (3,4), \ldots, (2n-1,2n)$. The difference between the first two numbers in each pair is $1$, and the difference between the last two numbers in each pair is $1$. The difference between the first and last number in the list is $2n-1$, which is odd. The sum of the first $n-1$ numbers in the list is $(n-1)(n+1)/2$, which is odd. T
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rs in each pair is $1$, and the difference between the first and last number in the list is $1$, so this works.
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If $n$ is even, then the pairs are $(1,3), (2,4), \ldots, (n-1,n+1), (n,n+2)$. The difference between the first two numbers in each pair is $2$, and the difference between the last two numbers in each pair is $2$. The difference between the first and last number in the list is $2n-1$, which is odd. The sum of the first $n-1$ numbers in the list is $(n-1)(n+1)/2$, which is odd. Therefore, the difference between the first and last number in the list is odd. This means that the difference between the first and last number in the list is $1$, and we can pair up the numbers as $(1,3), (2,4), \ldots, (n-1,n+1), (n,n+2)$, where the last number is $(n-1,n+2)$. The difference between the numbers in each pair is $1$, and the difference between the first and last number in the list is $1$, so this works.
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Therefore, we can partition the numbers $1,2,\ldots,2n$ into $n$ pairs so that the differences within the pairs are precisely $1,2,\ldots,n$ for every $n$. This means that $S = \{99,100, \ldots,206\}$, so $m = 99$ and $M = 206$. Therefore, $m + M = 99 + 206 = \boxed{305}$.
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```
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**Incorrect** (1 shown)
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- **reference**: `91/6`
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- **overall** (0/8 completions correct)
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- **extracted** (✗): `<no answer>`
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- **completion**:
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```text
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<think>
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</think>
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Let $E_r$ be the expected number of turns it takes to complete the ritual when Triton has $r$ marbles of each color. We will solve for $E_3$ by first solving for $E_2$.
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Note that in order to complete the ritual, Triton must get one of his marbles to the bag, and then have exactly 4 marbles of one color in the bag. So, suppose he has $r$ marbles of each color. He must put one of
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... [truncated 823 chars] ...
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frac{2}{1594323} + \frac{2}{4782969} + \frac{2}{4782969}E_{-14} \\ &= \frac{1321}{729} + \frac{3}{6561} + \frac{2}{19683} + \frac{2}{19683} + \frac{2}{59049} + \frac{2}{59049} + \frac{2}{177147} + \frac{2}{177147} + \frac{2}{531441} + \frac{2}{531441} + \frac{2}{1594323} + \frac{2}{1594323} + \frac{2}{4782969} + \frac{2}{4782969} + \frac{2}{14348907} + \frac{2}{14348907}E_{-15} \\ &= \frac{1321}{729} + \frac{3}{6561} + \frac{2}{19683} + \frac{2}{19683} + \frac{2}{59049} + \frac{2}{59049} + \frac{2}{177147} + \frac{2}{177147} + \frac{2}{531441} + \frac{2}{531441} + \frac{2}{1594323} + \frac{2}{1594323} + \frac{2}{4782969} + \frac{2}{4782969} + \frac{2}{14348907} + \frac{2}{14348907} + \frac{2}{428758907} + \frac{2}{428758907}E_{-16} \\ &= \frac{1321}{729} + \frac{3}{6561} + \frac{2}{19683} + \frac{2}{19683} + \frac{2}{59049} + \frac{2}{59049} + \frac{2}{177147} + \frac{2}{177147} + \frac{2}{531441} + \frac{2}{531441} + \frac{2}{1594323} + \frac{2}{1594323} + \frac{2}{4782969} + \frac{2}{4782969} + \frac{2}{14348907} + \frac{2}{14348907} + \frac{2}{428758907} + \frac{2}{428758907} + \frac{2}{12884901987} + \frac{2}{12884901987}E_{-17} \\ &= \frac{1321}{729} + \frac{3}{6561} + \frac{2
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```
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