Instructions to use cs-552-2026-baseline/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-baseline/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-baseline/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-baseline/general_knowledge_model") model = AutoModelForCausalLM.from_pretrained("cs-552-2026-baseline/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-baseline/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-baseline/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-baseline/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cs-552-2026-baseline/general_knowledge_model
- SGLang
How to use cs-552-2026-baseline/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-baseline/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-baseline/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-baseline/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-baseline/general_knowledge_model", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cs-552-2026-baseline/general_knowledge_model with Docker Model Runner:
docker model run hf.co/cs-552-2026-baseline/general_knowledge_model
Automated MNLP evaluation report (2026-06-01)
#1
by zechen-nlp - opened
- EVAL_REPORT.md +95 -0
EVAL_REPORT.md
ADDED
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# Automated MNLP evaluation report
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- **Model repo:** [`cs-552-2026-baseline/general_knowledge_model`](https://huggingface.co/cs-552-2026-baseline/general_knowledge_model)
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- **Owner(s):** group **baseline**
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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** β you do not need to merge it. The next nightly run will refresh this file._
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## Summary
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| Benchmark | Accuracy | Status |
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|---|---:|---|
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| Math | β | not run |
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| Knowledge | 0.2700 | ok |
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| Multilingual | β | not run |
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| Safety | β | 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**: `I`
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- **overall** (1/1 completions correct)
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- **extracted** (β): `I`
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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 credit term question. The term given is (7/10) EOM. I need to understand what this means.
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First, I remember that credit terms like 7/10 EOM are commonly used in business. The format is usually something like (discount percentage)/days allowed, followed by the EOM. So, the 7/10 part would mean a 7% discount if paid within 10 days of the end of the month.
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... [truncated 823 chars] ...
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r the end of the month"
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β Incorrect. The discount is 7%, not 10%.
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- **F.** "A customer may deduct 7% of the amount of the invoice if payment is made on the tenth day of the month"
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β Incorrect. The discount is not available on the 10th day of the month, but 10 days after the end of the month.
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- **G.** "A customer may deduct 10% of the amount of the invoice if payment is made no later than the seventh day of the month"
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β Incorrect. The discount is 7%, not 10%.
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- **H.** "A customer must pay the full amount of the invoice within 7 days of the end of the month"
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β Incorrect. This is not a credit term. The full payment is not required unless the discount is not taken.
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- **I.** "A customer may deduct 7% of the amount of the invoice if payment is made no later than the tenth day after the end of the month"
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β
**Correct.** This directly matches the meaning of the term **(7/10) EOM**, where the **7% discount is available within 10 days of the end of the month**.
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- **J.** "A customer may deduct 10% of the amount of the invoice if payment is made within 7 days of receiving the invoice"
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β Incorrect. The discount is 7%, not 10%.
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---
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### Final Answer:
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$$
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\boxed{I}
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$$
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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** (β): `<no answer>`
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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 Cope rearrangement problem. So, the question is about determining the major products of two reactions: one is a Cope rearrangement involving a 1,5-diene and some reagents, and the other is a heat-induced rearrangement of a compound. The choices are A, B, C, D, and I need to pick the correct one.
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First, let me recall what a Cope rearrangement is. From wha
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... [truncated 823 chars] ...
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ent, and the reaction is with BuLi and H+, maybe the reaction is a Grignard reaction. For example, if the substituent is a 1,2-diene, then the base (BuLi) might deprotonate the carbon adjacent to the double bond, forming a Grignard reagent, which then reacts with H+ to form a carbonyl. But I'm not sure.
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Alternatively, maybe the reaction is a hydroboration-oxidation, but that would require a different set of reagents.
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Alternatively, maybe the reaction is a Cope rearrangement. But the starting material is a 1,2-diene. Wait, the Cope rearrangement typically involves a 1,5-diene, so maybe the starting material is a 1,5-diene, but the structure given is different.
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Alternatively, maybe the reaction is a cyclopropane formation. Wait, but the question says that the Cope rearrangement involves a 1,5-diene.
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Alternatively, maybe the reaction is a Diels-Alder reaction, but that's not mentioned here.
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Alternatively, maybe the reaction is a nucleophilic substitution where the base deprotonates a carbon, leading to a carbonyl group. For example, if the substituent is a 1,2-diene, then the deprotonation might occur at the carbon adjacent to the double bond, leading to a carbonyl group.
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But
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```
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