Text Generation
Transformers
Safetensors
qwen3
Generated from Trainer
sft
trl
conversational
text-generation-inference
Instructions to use cs-552-2026-flab/general_knowledge_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs-552-2026-flab/general_knowledge_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cs-552-2026-flab/general_knowledge_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-flab/general_knowledge_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-flab/general_knowledge_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-flab/general_knowledge_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-flab/general_knowledge_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-flab/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-flab/general_knowledge_model
- SGLang
How to use cs-552-2026-flab/general_knowledge_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-flab/general_knowledge_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-flab/general_knowledge_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-flab/general_knowledge_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-flab/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-flab/general_knowledge_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-flab/general_knowledge_model
Update Automated MNLP evaluation report (2026-06-01)
Browse files- EVAL_REPORT.md +104 -10
EVAL_REPORT.md
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- **Model repo:** [`cs-552-2026-flab/general_knowledge_model`](https://huggingface.co/cs-552-2026-flab/general_knowledge_model)
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- **Owner(s):** group **flab**
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- **Generated at:** 2026-
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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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|---|---:|---|
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| Math | — | not run |
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| Knowledge | 0.
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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** (1/1 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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```
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**Incorrect** (1 shown)
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- **reference**: `
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- **overall** (0/1 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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```
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- **Model repo:** [`cs-552-2026-flab/general_knowledge_model`](https://huggingface.co/cs-552-2026-flab/general_knowledge_model)
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- **Owner(s):** group **flab**
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- **Generated at:** 2026-06-01T06:13:57+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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|---|---:|---|
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| Math | — | not run |
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| Knowledge | 0.4400 | ok |
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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**: `D`
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- **overall** (1/1 completions correct)
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- **extracted** (✓): `D`
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- **completion**:
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```text
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<think>
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Okay, let's try to figure out this problem. So, we have a solution that's 200.00 cm³, which is 0.200 liters. It contains 1.00 g of KH2PO4 and 1.00 g of Na2HPO4·2H2O. We need to find the concentration of orthophosphate ions, which I think is the phosphate ion, H2PO4^-? Wait, no. Wait, orthophosphate ions would be the phosphate ion, which is PO4^3-? Wait, no. Let me think. The problem says "
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The pH is determined using the Henderson-Hasselbalch equation for the buffer system:
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$$
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\text{pH} = \text{p}K_{a2} + \log\left(\frac{[\text{HPO}_4^{2-}]}{[\text{H}_2\text{PO}_4^-]}\right)
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$$
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- **pKa₂** (from the given Ka₂ = 6.2 × 10⁻⁸):
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$$
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\text{p}K_{a2} = -\log(6.2 \times 10^{-8}) \approx 7.21
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$$
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- **Ratio:**
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$$
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\frac{[\text{HPO}_4^{2-}]}{[\text{H}_2\text{PO}_4^-]} = \frac{0.0282}{0.036735} \approx 0.768
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$$
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- **pH:**
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$$
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\text{pH} = 7.21 + \log(0.768) \approx 7.21 - 0.113 = 7.097
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$$
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---
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### Step 4: Use the Ka₃ Expression to Find [PO₄³⁻]
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The dissociation reaction is:
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$$
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\text{HPO}_4^{2-} \rightleftharpoons \text{H}^+ + \text{PO}_4^{3-}
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$$
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The equilibrium expression is:
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$$
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K_{a3} = \frac{[\text{H}^+][\text{PO}_4^{3-}]}{[\text{HPO}_4^{2-}]}
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$$
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Solving for [PO₄³⁻]:
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$$
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[\text{PO}_4^{3-}] = \frac{K_{a3} \cdot [\text{HPO}_4^{2-}]}{[\text{H}^+]}
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$$
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- **Kₐ₃ = 1.8 × 10⁻¹²**
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- **[HPO₄²⁻] = 0.0282 M**
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- **[H⁺] = 10⁻⁷·⁰⁹⁷ ≈ 8.13 × 10⁻⁸ M**
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$$
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[\text{PO}_4^{3-}] = \frac{(1.8 \times 10^{-12}) \cdot 0.0282}{8.13 \times 10^{-8}} \approx \frac{5.076 \times 10^{-14}}{8.13 \times 10^{-8}} \approx 6.24 \times 10^{-7}\ \text{M}
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$$
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---
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### Final Answer
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$$
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\boxed{D}
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$$
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```
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**Incorrect** (1 shown)
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- **reference**: `A`
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- **overall** (0/1 completions correct)
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- **extracted** (✗): `H`
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- **completion**:
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```text
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<think>
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Okay, let's try to figure out the power spectral density (PSD) of the function f(t) given by the convolution of h(σ) and φ(t - σ). The question asks to express G_f(ω) in terms of G_φ(ω) and H(ω), where H(ω) is the Fourier transform of h(t).
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First, I remember that the power spectral density is related to the autocorrelation function, but here we have a convolution. Let me recall the prope
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... [truncated 822 chars] ...
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# Key Concepts
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1. **Convolution in Time Domain and Fourier Transform in Frequency Domain**:
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- The Fourier transform of the convolution of two functions is the product of their individual Fourier transforms:
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$$
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\mathcal{F}\{f(t)\} = \mathcal{F}\{h(t)\} \cdot \mathcal{F}\{\phi(t)\} = H(\omega) \cdot \Phi(\omega).
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$$
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2. **Power Spectral Density (PSD)**:
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- The **PSD** of a signal is the **Fourier transform of its autocorrelation function**.
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- For a linear system with impulse response $ h(t) $, the **PSD of the output** $ f(t) $ is given by:
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$$
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G_f(\omega) = |H(\omega)|^2 \cdot G_\phi(\omega),
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$$
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where:
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- $ G_\phi(\omega) $ is the power spectral density of $ \phi(t) $,
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- $ H(\omega) $ is the Fourier transform of $ h(t) $,
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- $ |H(\omega)|^2 $ is the power spectral density of $ h(t) $.
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---
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### Final Answer
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From the above reasoning, the correct expression for the power spectral density of $ f(t) $ is:
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$$
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G_f(\omega) = |H(\omega)|^2 \cdot G_\phi(\omega).
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$$
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However, none of the provided choices exactly match this expression. Among the given options, the **closest** and **most logically consistent** choice is:
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$$
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\boxed{H}
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$$
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```
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