Text Generation
Transformers
Safetensors
qwen3
Generated from Trainer
trl
sft
conversational
text-generation-inference
Instructions to use cs-552-2026-MandMP/math_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs-552-2026-MandMP/math_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cs-552-2026-MandMP/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-MandMP/math_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-MandMP/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-MandMP/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-MandMP/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-MandMP/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-MandMP/math_model
- SGLang
How to use cs-552-2026-MandMP/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-MandMP/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-MandMP/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-MandMP/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-MandMP/math_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-MandMP/math_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-MandMP/math_model
Commit ·
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Parent(s): 0f88a28
Automated MNLP evaluation report (2026-05-20) (#4)
Browse files- Automated MNLP evaluation report (2026-05-20) (241883a733d7ead36c20f71e469deb1f3e2de67d)
Co-authored-by: Zeming Chen - Eric <zechen-nlp@users.noreply.huggingface.co>
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EVAL_REPORT.md
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- **Model repo:** [`cs-552-2026-MandMP/math_model`](https://huggingface.co/cs-552-2026-MandMP/math_model)
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- **Owner(s):** group **MandMP**
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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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- **completion**:
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```text
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Okay, so I need to solve the equation 10^x minus 10 equals 9990. Let me write that down first: 10^x - 10 = 9990. Hmm, let me think about how to approach this.
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10^x - 10 + 10 = 9990 + 10
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Simplifying b
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But just to be absolutely sure, let me check with another method. Let's say I use natural logarithm.
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Starting with 10^x = 10,000. Taking natural logarithm on both sides:
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ln(10^x) = ln(10,000)
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x =
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Same result.
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Therefore, regardless of the method, x is 4.
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So, I think that's solid.
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Therefore, the solution is x = 4.
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**Final Answer**
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The solution is \boxed{4}.
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10^x - 10 = 9990
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$$
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$$
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10^x - 10 + 10 = 9990 + 10
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10^x =
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x = 4
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10^4 - 10 =
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This matches the right-hand side of the original equation, confirming that the solution is correct.
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\boxed{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** (✗): `<no answer>`
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- **completion**:
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```text
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```
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- **Model repo:** [`cs-552-2026-MandMP/math_model`](https://huggingface.co/cs-552-2026-MandMP/math_model)
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- **Owner(s):** group **MandMP**
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- **Generated at:** 2026-05-20T05:49:46+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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- **completion**:
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```text
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Okay, so I need to solve the equation 10^x minus 10 equals 9990. Let me write that down first to make sure I have it right: 10^x - 10 = 9990. Alright, so my goal is to find the value of x that satisfies this equation.
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Hmm, let me think. I know that 10^x is a common exponential expression, and since the base is 10, maybe I can manipulate this equation to solve for x. Let me start by isolating the
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ation: 10^x - 10 = 9990
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Add 10 to both sides: 10^x = 10,000
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Recognize that 10,000 is 10^4, so x = 4
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Check by substitution: 10^4 - 10 = 10,000 - 10 = 9,990, which matches the right side.
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Therefore, all steps are consistent and correct.
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I think that's thorough enough. I don't see any mistakes in my reasoning, and the answer checks out when substituted back into the original equation. So, I think x = 4 is the correct solution.
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**Final Answer**
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The solution is \boxed{4}.
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10^x - 10 = 9990
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$$
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---
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### Step 1: Isolate the Exponential Term
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We begin by isolating the exponential term $ 10^x $ by adding 10 to both sides of the equation:
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10^x - 10 + 10 = 9990 + 10
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$$
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$$
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10^x = 10,000
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---
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### Step 2: Recognize the Exponential Form
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Now that we have:
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10^x = 10,000
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we recognize that $ 10,000 = 10^4 $. Therefore, we can equate the exponents:
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$$
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x = 4
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### Step 3: Verify the Solution
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To confirm, substitute $ x = 4 $ back into the original equation:
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10^4 - 10 = 10,000 - 10 = 9,990
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$$
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This matches the right-hand side of the original equation, confirming that the solution is correct.
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### Final Answer
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$$
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\boxed{4}
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**Incorrect** (1 shown)
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- **reference**: `1012`
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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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Okay, so I need to find the maximum possible value of the sum $\sum_{i=1}^{2023} \frac{a_i - a_{i-1}}{a_{i+1} - a_i}$, given that $a_0 = 0$ and each $a_{i+1} \geq 2a_i$ for $i = 1, 2, \ldots, 2023$. All the $a_i$ are positive real numbers.
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First, let me parse the problem. The variables are $a_1$ through $a_{2024}$, with $a_0 = 0$. The condition is that each subsequent term is at least twice the
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i=1}^{2023} \frac{a_i - a_{i-1}}{a_{i+1} - a_i}$." So, the sum has 2023 terms, each involving $a_i - a_{i-1}$ and $a_{i+1} - a_i$.
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So, for n=2024, there are 2023 terms. So, the problem is for n=2024, with 2023 terms.
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But in my earlier examples with n=2 and n=3, the maximum was achieved when the sequence was constant.
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But let me think again. Suppose that for some i, we make b_{i+1} larger than b_i, then we have to make b_{i+2} larger than b_{i+1}, etc., which would make the subsequent terms smaller. However, if we make some b_i's larger and some smaller? But since the sequence must be non-decreasing, we can't make some b_i's smaller.
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Therefore, the only way to maximize the sum is to have all the b_i's equal.
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But let me think again. Suppose that for some i, we have b_{i+1} = b_i, and for other terms, b_{i+1} is larger. But since the sequence is non-decreasing, once we have b_{i+1} larger than b_i, we can't make it smaller. Therefore, the sequence is non-decreasing, so if we have some b_i's equal, and others larger, but the sum would be less than if all are equal.
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Therefore, the maximum is achieved when all b_i's are equal.
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Therefore, the maximum value of the sum is 2023
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```
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