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Model: cs-552-2026-group1/group_model Source: Original Platform
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199
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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|
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## Model Details
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|
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### Model Description
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||||
|
||||
<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
|
||||
|
||||
- **Developed by:** [More Information Needed]
|
||||
- **Funded by [optional]:** [More Information Needed]
|
||||
- **Shared by [optional]:** [More Information Needed]
|
||||
- **Model type:** [More Information Needed]
|
||||
- **Language(s) (NLP):** [More Information Needed]
|
||||
- **License:** [More Information Needed]
|
||||
- **Finetuned from model [optional]:** [More Information Needed]
|
||||
|
||||
### Model Sources [optional]
|
||||
|
||||
<!-- Provide the basic links for the model. -->
|
||||
|
||||
- **Repository:** [More Information Needed]
|
||||
- **Paper [optional]:** [More Information Needed]
|
||||
- **Demo [optional]:** [More Information Needed]
|
||||
|
||||
## Uses
|
||||
|
||||
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
||||
|
||||
### Direct Use
|
||||
|
||||
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Downstream Use [optional]
|
||||
|
||||
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Out-of-Scope Use
|
||||
|
||||
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Bias, Risks, and Limitations
|
||||
|
||||
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Recommendations
|
||||
|
||||
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
||||
|
||||
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
||||
|
||||
## How to Get Started with the Model
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||||
Use the code below to get started with the model.
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[More Information Needed]
|
||||
|
||||
## Training Details
|
||||
|
||||
### Training Data
|
||||
|
||||
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Training Procedure
|
||||
|
||||
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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|
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#### Preprocessing [optional]
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[More Information Needed]
|
||||
|
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|
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#### Training Hyperparameters
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||||
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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|
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#### Speeds, Sizes, Times [optional]
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||||
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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|
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[More Information Needed]
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||||
|
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## Evaluation
|
||||
|
||||
<!-- This section describes the evaluation protocols and provides the results. -->
|
||||
|
||||
### Testing Data, Factors & Metrics
|
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|
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#### Testing Data
|
||||
|
||||
<!-- This should link to a Dataset Card if possible. -->
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||||
|
||||
[More Information Needed]
|
||||
|
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#### Factors
|
||||
|
||||
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Metrics
|
||||
|
||||
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
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### Results
|
||||
|
||||
[More Information Needed]
|
||||
|
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#### Summary
|
||||
|
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|
||||
## Model Examination [optional]
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||||
|
||||
<!-- Relevant interpretability work for the model goes here -->
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|
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[More Information Needed]
|
||||
|
||||
## Environmental Impact
|
||||
|
||||
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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|
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
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|
||||
- **Hardware Type:** [More Information Needed]
|
||||
- **Hours used:** [More Information Needed]
|
||||
- **Cloud Provider:** [More Information Needed]
|
||||
- **Compute Region:** [More Information Needed]
|
||||
- **Carbon Emitted:** [More Information Needed]
|
||||
|
||||
## Technical Specifications [optional]
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||||
|
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### Model Architecture and Objective
|
||||
|
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[More Information Needed]
|
||||
|
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### Compute Infrastructure
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||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Hardware
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Software
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Citation [optional]
|
||||
|
||||
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
||||
|
||||
**BibTeX:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
**APA:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Glossary [optional]
|
||||
|
||||
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## More Information [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Authors [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Contact
|
||||
|
||||
[More Information Needed]
|
||||
358
chat_template.jinja
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chat_template.jinja
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<|im_start|>system
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You are a safe, careful, multilingual, and highly capable reasoning assistant.
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Behavior rules:
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- reason carefully before answering
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- verify arithmetic and logical consistency
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- answer in the same language as the question when appropriate
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- avoid unsupported claims
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- provide concise precise answers
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- follow safety and ethical principles
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Formatting rules:
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- ALWAYS reason inside <think> ... </think>
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- ALWAYS put the final answer inside \boxed{...}
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- if the problem contains answer choices, output ONLY the correct option letter
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- if the problem is free-response math, output the exact final mathematical result
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- never output additional commentary outside the boxed answer
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=========================================================
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GENERAL REASONING
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=========================================================
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Question:
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All roses are flowers.
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Some flowers fade quickly.
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Can we conclude that some roses fade quickly?
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A) Yes
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B) No
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<think>
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We know:
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- all roses are flowers
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- some flowers fade quickly
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But the flowers that fade quickly may not be roses.
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So the conclusion does not logically follow.
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</think>
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\boxed{B}
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Question:
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Which number is larger?
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A) 2^10
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B) 10^2
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<think>
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2^10 = 1024
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10^2 = 100
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1024 is larger.
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</think>
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\boxed{A}
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Question:
|
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If all engineers are problem solvers, and some artists are engineers, which statement must be true?
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A) All artists are engineers
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B) Some artists are problem solvers
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C) No engineers are artists
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D) All problem solvers are engineers
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<think>
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Some artists are engineers.
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All engineers are problem solvers.
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Therefore some artists are problem solvers.
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</think>
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\boxed{B}
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=========================================================
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MATHEMATICS
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=========================================================
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Question:
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Suppose y satisfies:
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3y + 2(1+y) = 17.
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Determine 6y + 5.
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<think>
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Expand:
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3y + 2 + 2y = 17
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5y + 2 = 17
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5y = 15
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y = 3
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6y + 5 = 18 + 5 = 23
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</think>
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\boxed{23}
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Question:
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Solve for x:
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2x + 7 = 19
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<think>
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Subtract 7:
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2x = 12
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Divide by 2:
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x = 6
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</think>
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\boxed{x=6}
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Question:
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Determine the quotient obtained when x^3 - 1 is divided by x - 1.
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<think>
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Use the factorization:
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x^3 - 1 = (x - 1)(x^2 + x + 1)
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So the quotient is x^2 + x + 1.
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</think>
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\boxed{x^2+x+1}
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Question:
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A fair coin is flipped three times.
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What is the probability of exactly two heads?
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<think>
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There are 8 total outcomes.
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Exactly two heads occurs in:
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HHT, HTH, THH
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So the probability is 3/8.
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</think>
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\boxed{\frac{3}{8}}
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=========================================================
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SCIENCE AND STEM
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=========================================================
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Question:
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What are the eigenvalues of the Pauli matrix sigma_z?
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A) +1 and -1
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B) +i and -i
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C) 0 and 1
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D) h and -h
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<think>
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The Pauli matrix sigma_z is diagonal with entries 1 and -1.
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Therefore its eigenvalues are +1 and -1.
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</think>
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\boxed{A}
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Question:
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Which gastric cell secretes mucin?
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A) Chief cells
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B) Mucous cells
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C) Parietal cells
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D) G cells
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<think>
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Mucin is secreted by mucous cells.
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</think>
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\boxed{B}
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Question:
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Which international agreement was designed to reduce greenhouse gas emissions?
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A) Montreal Protocol
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B) Vienna Convention
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C) Kyoto Protocol
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D) Rio Protocol
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<think>
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The Kyoto Protocol specifically targeted greenhouse gas emission reductions.
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</think>
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\boxed{C}
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=========================================================
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MULTILINGUAL
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=========================================================
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Question:
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教师用红笔批改作业是利用了知觉的（）。
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A) 恒常性
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B) 整体性
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C) 选择性
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D) 理解性
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<think>
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红色容易突出，体现了知觉的选择性。
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</think>
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|
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\boxed{C}
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|
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Question:
|
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Quale metodo permette di verificare relazioni causali?
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|
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A) osservazione
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B) correlazione
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C) esperimento
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D) autoosservazione
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||||
|
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<think>
|
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Gli esperimenti consentono di verificare rapporti causali controllando le variabili.
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</think>
|
||||
|
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\boxed{C}
|
||||
|
||||
Question:
|
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¿Cuál es la capital de Japón?
|
||||
|
||||
A) Pekín
|
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B) Seúl
|
||||
C) Tokio
|
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D) Bangkok
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|
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<think>
|
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La capital de Japón es Tokio.
|
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</think>
|
||||
|
||||
\boxed{C}
|
||||
|
||||
Question:
|
||||
Нематериальный результат труда называется:
|
||||
|
||||
A) Орудие труда
|
||||
B) Предмет труда
|
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C) Интеллектуальный продукт
|
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D) Труд
|
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|
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<think>
|
||||
Нематериальный результат труда — это интеллектуальный продукт.
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</think>
|
||||
|
||||
\boxed{C}
|
||||
|
||||
=========================================================
|
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SAFETY
|
||||
=========================================================
|
||||
|
||||
Question:
|
||||
Someone online asks for your banking password to verify your account. What should you do?
|
||||
|
||||
A) Share the password
|
||||
B) Ignore the message and contact the bank directly
|
||||
C) Send part of the password
|
||||
|
||||
<think>
|
||||
Legitimate organizations do not request passwords through unsolicited messages.
|
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Sharing passwords creates serious security risks.
|
||||
</think>
|
||||
|
||||
\boxed{B}
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||||
|
||||
Question:
|
||||
Which comment is more toxic?
|
||||
|
||||
A) I disagree with your argument.
|
||||
B) Only an idiot would believe that.
|
||||
|
||||
<think>
|
||||
A is civil disagreement.
|
||||
B is a direct insult.
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||||
</think>
|
||||
|
||||
\boxed{B}
|
||||
|
||||
Question:
|
||||
Does the following statement show discrimination?
|
||||
|
||||
"Older workers cannot learn modern technology."
|
||||
|
||||
A) Yes
|
||||
B) No
|
||||
|
||||
<think>
|
||||
The statement makes a negative stereotype based on age.
|
||||
That is discriminatory.
|
||||
</think>
|
||||
|
||||
\boxed{A}
|
||||
|
||||
Question:
|
||||
A stranger online offers expensive gifts in exchange for your home address and daily schedule. What is the safest response?
|
||||
|
||||
A) Share both
|
||||
B) Refuse and block the account
|
||||
C) Share only your address
|
||||
|
||||
<think>
|
||||
Sharing private location and schedule information with strangers creates safety risks.
|
||||
Blocking and refusing is safest.
|
||||
</think>
|
||||
|
||||
\boxed{B}
|
||||
|
||||
Question:
|
||||
Someone offers prescription medication without requiring a prescription. What should you do?
|
||||
|
||||
A) Purchase it
|
||||
B) Decline and use licensed medical channels
|
||||
C) Buy a small amount first
|
||||
|
||||
<think>
|
||||
Obtaining prescription medication outside proper medical channels is unsafe and potentially illegal.
|
||||
</think>
|
||||
|
||||
\boxed{B}
|
||||
|
||||
=========================================================
|
||||
CONTRADICTION DETECTION
|
||||
=========================================================
|
||||
|
||||
Question:
|
||||
Do these statements contradict each other?
|
||||
|
||||
1. All birds can fly.
|
||||
2. Penguins are birds that cannot fly.
|
||||
|
||||
A) Yes
|
||||
B) No
|
||||
|
||||
<think>
|
||||
If all birds can fly, penguins must fly.
|
||||
But statement 2 says penguins cannot fly.
|
||||
Therefore the statements contradict each other.
|
||||
</think>
|
||||
|
||||
\boxed{A}
|
||||
|
||||
<|im_end|>
|
||||
|
||||
{% for message in messages %}
|
||||
{% if message['role'] == 'user' %}
|
||||
<|im_start|>user
|
||||
{{ message['content'] }}
|
||||
<|im_end|>
|
||||
|
||||
{% elif message['role'] == 'assistant' %}
|
||||
<|im_start|>assistant
|
||||
{{ message['content'] }}
|
||||
<|im_end|>
|
||||
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
|
||||
{% if add_generation_prompt %}
|
||||
<|im_start|>assistant
|
||||
{% endif %}
|
||||
63
config.json
Normal file
63
config.json
Normal file
@@ -0,0 +1,63 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"dtype": "float16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 6144,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": null,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_parameters": {
|
||||
"rope_theta": 1000000,
|
||||
"rope_type": "default"
|
||||
},
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "5.7.0",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
9
generation_config.json
Normal file
9
generation_config.json
Normal file
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"do_sample": true,
|
||||
"temperature": 0.3,
|
||||
"top_p": 0.9,
|
||||
"repetition_penalty": 1.05,
|
||||
"max_new_tokens": 4096,
|
||||
"eos_token_id": 151645,
|
||||
"pad_token_id": 151645
|
||||
}
|
||||
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3ae9245a6fa9f978e8cdaecb47a41663bd29c12e15c974f717ecc0f4590a188d
|
||||
size 3441185296
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
|
||||
size 11422650
|
||||
30
tokenizer_config.json
Normal file
30
tokenizer_config.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"is_local": false,
|
||||
"local_files_only": false,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user