Instructions to use cookinai/OpenCM-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cookinai/OpenCM-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cookinai/OpenCM-14", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cookinai/OpenCM-14") model = AutoModelForCausalLM.from_pretrained("cookinai/OpenCM-14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use cookinai/OpenCM-14 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cookinai/OpenCM-14" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cookinai/OpenCM-14", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cookinai/OpenCM-14
- SGLang
How to use cookinai/OpenCM-14 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 "cookinai/OpenCM-14" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cookinai/OpenCM-14", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "cookinai/OpenCM-14" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cookinai/OpenCM-14", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use cookinai/OpenCM-14 with Docker Model Runner:
docker model run hf.co/cookinai/OpenCM-14
Adding Evaluation Results
#1
by leaderboard-pr-bot - opened
README.md
CHANGED
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@@ -2,9 +2,125 @@
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license: cc-by-nc-4.0
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tags:
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- merge
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---
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Finetune of **cookinai/CM-14** with the **teknium/openhermes** dataset. My first finetune, might have some bugs/overfitting, might reupload
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Previous model had stopping token errors causing issues with the final token in the ChatML preset. This finetuning job should fix any prompt template errors. Please tell me if you get any such errors.
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-
Heard that this error is common amongst heavily merged macaroni models. Might try to stray away from them in the future or dilute them with other models.
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license: cc-by-nc-4.0
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tags:
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- merge
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+
model-index:
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- name: OpenCM-14
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results:
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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+
value: 69.28
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+
name: normalized accuracy
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+
source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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name: Text Generation
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+
dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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+
metrics:
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- type: acc_norm
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value: 86.89
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name: normalized accuracy
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+
source:
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+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 65.01
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name: accuracy
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+
source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 61.07
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 81.29
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name: accuracy
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source:
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| 89 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 72.93
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name: accuracy
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| 105 |
+
source:
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| 106 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cookinai/OpenCM-14
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| 107 |
+
name: Open LLM Leaderboard
|
| 108 |
---
|
| 109 |
Finetune of **cookinai/CM-14** with the **teknium/openhermes** dataset. My first finetune, might have some bugs/overfitting, might reupload
|
| 110 |
|
| 111 |
Previous model had stopping token errors causing issues with the final token in the ChatML preset. This finetuning job should fix any prompt template errors. Please tell me if you get any such errors.
|
| 112 |
|
| 113 |
+
Heard that this error is common amongst heavily merged macaroni models. Might try to stray away from them in the future or dilute them with other models.
|
| 114 |
+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_cookinai__OpenCM-14)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |72.75|
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|AI2 Reasoning Challenge (25-Shot)|69.28|
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|HellaSwag (10-Shot) |86.89|
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|MMLU (5-Shot) |65.01|
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|TruthfulQA (0-shot) |61.07|
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| 124 |
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|Winogrande (5-shot) |81.29|
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| 125 |
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|GSM8k (5-shot) |72.93|
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| 126 |
+
|