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Abhaykoul_-_Qwen1.5-0.5B-vortex-0.1-gguf – AI Model by RichardErkhov | AlphaNeural AI
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Qwen1.5-0.5B-vortex-0.1 - GGUF
Model creator:
https://huggingface.co/Abhaykoul/
Original model:
https://huggingface.co/Abhaykoul/Qwen1.5-0.5B-vortex-0.1/
Name
Quant method
Size
Qwen1.5-0.5B-vortex-0.1.Q2_K.gguf
Q2_K
0.23GB
Qwen1.5-0.5B-vortex-0.1.IQ3_XS.gguf
IQ3_XS
0.24GB
Qwen1.5-0.5B-vortex-0.1.IQ3_S.gguf
IQ3_S
0.25GB
Qwen1.5-0.5B-vortex-0.1.Q3_K_S.gguf
Q3_K_S
0.25GB
Qwen1.5-0.5B-vortex-0.1.IQ3_M.gguf
IQ3_M
0.26GB
Qwen1.5-0.5B-vortex-0.1.Q3_K.gguf
Q3_K
0.26GB
Qwen1.5-0.5B-vortex-0.1.Q3_K_M.gguf
Q3_K_M
0.26GB
Qwen1.5-0.5B-vortex-0.1.Q3_K_L.gguf
Q3_K_L
0.28GB
Qwen1.5-0.5B-vortex-0.1.IQ4_XS.gguf
IQ4_XS
0.28GB
Qwen1.5-0.5B-vortex-0.1.Q4_0.gguf
Q4_0
0.29GB
Qwen1.5-0.5B-vortex-0.1.IQ4_NL.gguf
IQ4_NL
0.29GB
Qwen1.5-0.5B-vortex-0.1.Q4_K_S.gguf
Q4_K_S
0.29GB
Qwen1.5-0.5B-vortex-0.1.Q4_K.gguf
Q4_K
0.3GB
Qwen1.5-0.5B-vortex-0.1.Q4_K_M.gguf
Q4_K_M
0.3GB
Qwen1.5-0.5B-vortex-0.1.Q4_1.gguf
Q4_1
0.3GB
Qwen1.5-0.5B-vortex-0.1.Q5_0.gguf
Q5_0
0.32GB
Qwen1.5-0.5B-vortex-0.1.Q5_K_S.gguf
Q5_K_S
0.32GB
Qwen1.5-0.5B-vortex-0.1.Q5_K.gguf
Q5_K
0.33GB
Qwen1.5-0.5B-vortex-0.1.Q5_K_M.gguf
Q5_K_M
0.33GB
Qwen1.5-0.5B-vortex-0.1.Q5_1.gguf
Q5_1
0.34GB
Qwen1.5-0.5B-vortex-0.1.Q6_K.gguf
Q6_K
0.36GB
Qwen1.5-0.5B-vortex-0.1.Q8_0.gguf
Q8_0
0.47GB
Original model description:
language:
en license: other datasets:
OEvortex/vortex-mini
yahma/alpaca-cleaned license_name: tongyi-qianwen-research license_link:
https://huggingface.co/Qwen/Qwen1.5-0.5B/blob/main/LICENSE
pipeline_tag: text-generation model-index:
name: Qwen1.5-0.5B-vortex-v2 results:
task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
type: acc_norm value: 30.63 name: normalized accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
type: acc_norm value: 45.54 name: normalized accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
type: acc value: 36.29 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
type: mc2 value: 44.29 source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
type: acc value: 56.04 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
type: acc value: 5.91 name: accuracy source: url:
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Abhaykoul/Qwen1.5-0.5B-vortex-v2
name: Open LLM Leaderboard
Qwen1.5-0.5B-vortex-v2 model card
Qwen1.5-0.5B-vortex-v2 is a dealigned chat finetune of the original fantastic Qwen1.5-0.5B model by the Qwen team.
This model was trained on the Vortex mini dataset and alpaca-cleaned using axolotl for 4 epoch
Open LLM Leaderboard Evaluation Results
Detailed results can be found
here
Metric
Value
Avg.
36.45
AI2 Reasoning Challenge (25-Shot)
30.63
HellaSwag (10-Shot)
45.54
MMLU (5-Shot)
36.29
TruthfulQA (0-shot)
44.29
Winogrande (5-shot)
56.04
GSM8k (5-shot)
5.91