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RichardErkhov/
MaziyarPanahi_-_calme-2.4-qwen2-7b-gguf

Name: MaziyarPanahi_-_calme-2.4-qwen2-7b-gguf
Availability: InStock

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calme-2.4-qwen2-7b - GGUF

Model creator: https://huggingface.co/MaziyarPanahi/
Original model: https://huggingface.co/MaziyarPanahi/calme-2.4-qwen2-7b/

Name	Quant method	Size
calme-2.4-qwen2-7b.Q2_K.gguf	Q2_K	2.81GB
calme-2.4-qwen2-7b.IQ3_XS.gguf	IQ3_XS	3.12GB
calme-2.4-qwen2-7b.IQ3_S.gguf	IQ3_S	3.26GB
calme-2.4-qwen2-7b.Q3_K_S.gguf	Q3_K_S	3.25GB
calme-2.4-qwen2-7b.IQ3_M.gguf	IQ3_M	3.33GB
calme-2.4-qwen2-7b.Q3_K.gguf	Q3_K	3.55GB
calme-2.4-qwen2-7b.Q3_K_M.gguf	Q3_K_M	3.55GB
calme-2.4-qwen2-7b.Q3_K_L.gguf	Q3_K_L	3.81GB
calme-2.4-qwen2-7b.IQ4_XS.gguf	IQ4_XS	3.96GB
calme-2.4-qwen2-7b.Q4_0.gguf	Q4_0	4.13GB
calme-2.4-qwen2-7b.IQ4_NL.gguf	IQ4_NL	4.16GB
calme-2.4-qwen2-7b.Q4_K_S.gguf	Q4_K_S	4.15GB
calme-2.4-qwen2-7b.Q4_K.gguf	Q4_K	4.36GB
calme-2.4-qwen2-7b.Q4_K_M.gguf	Q4_K_M	4.36GB
calme-2.4-qwen2-7b.Q4_1.gguf	Q4_1	4.54GB
calme-2.4-qwen2-7b.Q5_0.gguf	Q5_0	4.95GB
calme-2.4-qwen2-7b.Q5_K_S.gguf	Q5_K_S	4.95GB
calme-2.4-qwen2-7b.Q5_K.gguf	Q5_K	5.07GB
calme-2.4-qwen2-7b.Q5_K_M.gguf	Q5_K_M	5.07GB
calme-2.4-qwen2-7b.Q5_1.gguf	Q5_1	5.36GB
calme-2.4-qwen2-7b.Q6_K.gguf	Q6_K	5.82GB
calme-2.4-qwen2-7b.Q8_0.gguf	Q8_0	7.54GB

Original model description:

language:

en license: apache-2.0 library_name: transformers tags:
chat
qwen
qwen2
finetune
chatml
OpenHermes-2.5
HelpSteer2
Orca
SlimOrca base_model: Qwen/Qwen2-7B datasets:
nvidia/HelpSteer2
teknium/OpenHermes-2.5
microsoft/orca-math-word-problems-200k
Open-Orca/SlimOrca model_name: calme-2.4-qwen2-7b pipeline_tag: text-generation inference: false model_creator: MaziyarPanahi quantized_by: MaziyarPanahi model-index:
name: calme-2.4-qwen2-7b results:
- task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics:
  - type: inst_level_strict_acc and prompt_level_strict_acc value: 33.0 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics:
  - type: acc_norm value: 31.82 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics:
  - type: exact_match value: 18.35 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics:
  - type: acc_norm value: 4.47 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics:
  - type: acc_norm value: 14.43 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics:
  - type: acc value: 33.08 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-2.4-qwen2-7b name: Open LLM Leaderboard

MaziyarPanahi/calme-2.4-qwen2-7b

This is a fine-tuned version of the Qwen/Qwen2-7B model. It aims to improve the base model across all benchmarks.

⚡ Quantized GGUF

All GGUF models are available here: MaziyarPanahi/calme-2.4-qwen2-7b-GGUF

🏆 Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	22.52
IFEval (0-Shot)	33.00
BBH (3-Shot)	31.82
MATH Lvl 5 (4-Shot)	18.35
GPQA (0-shot)	4.47
MuSR (0-shot)	14.43
MMLU-PRO (5-shot)	33.08

Prompt Template

This model uses ChatML prompt template:

<|im_start|>system
{System}
<|im_end|>
<|im_start|>user
{User}
<|im_end|>
<|im_start|>assistant
{Assistant}

How to use

python

# Use a pipeline as a high-level helper

from transformers import pipeline

messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="MaziyarPanahi/calme-2.4-qwen2-7b")
pipe(messages)


# Load model directly

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-2.4-qwen2-7b")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-2.4-qwen2-7b")

RichardErkhov/MaziyarPanahi_-_calme-2.4-qwen2-7b-gguf