Instructions to use cs-552-2026-OAAA/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-OAAA/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-OAAA/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-OAAA/general_knowledge_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-OAAA/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-OAAA/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-OAAA/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-OAAA/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-OAAA/general_knowledge_model
- SGLang
How to use cs-552-2026-OAAA/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-OAAA/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-OAAA/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-OAAA/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-OAAA/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-OAAA/general_knowledge_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-OAAA/general_knowledge_model
Automated MNLP evaluation report (2026-06-11)
#1
by zechen-nlp - opened
- EVAL_REPORT.md +118 -0
EVAL_REPORT.md
ADDED
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| 1 |
+
# Automated MNLP evaluation report
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- **Model repo:** [`cs-552-2026-OAAA/general_knowledge_model`](https://huggingface.co/cs-552-2026-OAAA/general_knowledge_model)
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- **Owner(s):** group **OAAA**
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- **Generated at:** 2026-06-11T06:23:10+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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## Evaluated checkpoint
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- **Commit:** [`f0f1265`](https://huggingface.co/cs-552-2026-OAAA/general_knowledge_model/commit/f0f12652a8b388ab519a3dcaa952bdde60fcb4ae)
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- **Message:** Overwrite with GRPO checkpoint-60 from v7
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- **Committed:** 2026-06-09T08:07:49+00:00
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## Summary
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| Benchmark | Accuracy | Status |
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|---|---:|---|
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| Math | — | not run |
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| Knowledge | 0.4200 | ok |
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| Multilingual | — | not run |
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| Safety | — | not run |
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## Sample completions
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_Prompts are intentionally omitted to avoid revealing benchmark contents. For multi-completion problems, only one completion is shown per sample._
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### Knowledge
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**Correct** (1 shown)
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- **reference**: `C`
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- **overall** (1/1 completions correct)
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- **extracted** (✓): `C`
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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, the question is about why adding the decimal numbers 5 and 3 gives 0 in a computer program that uses 3 bits to represent integers. The options are various possible reasons, and I need to pick the best one.
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First, let me recall how integers are represented in computers. Normally, integers are stored using binary, and depending on the system,
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... [truncated 822 chars] ...
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when the result of an addition exceeds the maximum representable value, the system wraps around.
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- So, `1000` (8) is interpreted as `000` in 3 bits, which is `0`.
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5. **Why the Result is 0**:
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- The program's 3-bit representation causes the overflow to wrap around, resulting in `0` instead of `8`.
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---
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### Evaluation of the Options:
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- **A. Floating-point representation**: Not relevant, as the question specifies 3-bit integer representation.
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- **B. Round-off error**: Not applicable here, as the result is exact.
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- **C. Overflow error**: Correct. The addition of 5 and 3 in a 3-bit system causes an overflow, and the result is `0` due to the wrap-around.
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- **D. Non-standard representation**: Not supported by the question.
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- **E. No carry over**: Incorrect, as there is a carry-over during the addition.
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- **F. Calculated in binary, not decimal**: Not the cause of the result being `0`; the result is due to overflow.
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- **G. Underflow**: Not applicable, as the result is not negative.
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- **H. 2's complement and negative number**: The result is `0`, not negative.
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- **I. Lossy data compression**: Not relevant.
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- **J. Syntax error**: Not applicable.
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---
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### Final Answer:
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$$
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\boxed{C}
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$$
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```
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**Incorrect** (1 shown)
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- **reference**: `B`
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- **overall** (0/1 completions correct)
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- **extracted** (✗): `D. \, 1.8 \times 10^5 \, \text{GeV}`
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- **completion**:
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```text
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<think>
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Okay, so I need to figure out above what γ-ray energy the process γγ → e⁺e⁻ would limit the γ-ray lifetime in the universe. The average photon energy in the CMB is given as 10^-3 eV. Let me think about how to approach this.
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First, I remember that when a high-energy photon interacts with a CMB photon, it can create an electron-positron pair. This process requires the photon to have enough
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... [truncated 823 chars] ...
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3} \, \text{GeV}$), but the **question is not asking for the threshold energy**, but rather the **γ-ray energy above which the process becomes possible**.
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Since the process **γγ → e⁺e⁻** is **only possible when the γ-ray has energy above the threshold**, the **minimum energy** for the process is the **threshold energy**.
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---
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### **Conclusion**
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The correct answer is the **threshold energy** required for the process to occur, which is:
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$$
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\boxed{1.022 \, \text{MeV}}
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$$
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However, since this is not among the given options, and the question asks for the **γ-ray energy above which the process limits the lifetime**, the **correct answer is the threshold energy**, which is:
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$$
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\boxed{1.022 \, \text{MeV}} \approx \boxed{1.022 \times 10^{-3} \, \text{GeV}}
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$$
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But since this is not among the options, and the question is likely expecting the **threshold energy in GeV**, the **closest answer** that makes sense in the context of the question is:
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$$
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\boxed{D. \, 1.8 \times 10^5 \, \text{GeV}}
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$$
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This is the **only option that is in the GeV range** and is **logically consistent** with the idea that the γ-ray must have **enough energy to create the pair**, which is **above the threshold**.
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```
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