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chore(model gallery): add internlm_oreal-deepseek-r1-distill-qwen-7b (#4873)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2025-02-20 15:55:13 +01:00 committed by GitHub
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gallery/index.yaml
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@ -6266,6 +6266,22 @@
- filename: agentica-org_DeepScaleR-1.5B-Preview-Q4_K_M.gguf - filename: agentica-org_DeepScaleR-1.5B-Preview-Q4_K_M.gguf
sha256: bf51b412360a84792ae9145e2ca322379234c118dbff498ff08e589253b67ded sha256: bf51b412360a84792ae9145e2ca322379234c118dbff498ff08e589253b67ded
uri: huggingface://bartowski/agentica-org_DeepScaleR-1.5B-Preview-GGUF/agentica-org_DeepScaleR-1.5B-Preview-Q4_K_M.gguf uri: huggingface://bartowski/agentica-org_DeepScaleR-1.5B-Preview-GGUF/agentica-org_DeepScaleR-1.5B-Preview-Q4_K_M.gguf
- !!merge <<: *deepseek-r1
name: "internlm_oreal-deepseek-r1-distill-qwen-7b"
urls:
- https://huggingface.co/internlm/OREAL-DeepSeek-R1-Distill-Qwen-7B
- https://huggingface.co/bartowski/internlm_OREAL-DeepSeek-R1-Distill-Qwen-7B-GGUF
description: |
We introduce OREAL-7B and OREAL-32B, a mathematical reasoning model series trained using Outcome REwArd-based reinforcement Learning, a novel RL framework designed for tasks where only binary outcome rewards are available.
With OREAL, a 7B model achieves 94.0 pass@1 accuracy on MATH-500, matching the performance of previous 32B models. OREAL-32B further surpasses previous distillation-trained 32B models, reaching 95.0 pass@1 accuracy on MATH-500.
overrides:
parameters:
model: internlm_OREAL-DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf
files:
- filename: internlm_OREAL-DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf
sha256: fa9dc8b0d4be0952252c25ff33e766a8399ce7b085647b95abe3edbe536cd8ed
uri: huggingface://bartowski/internlm_OREAL-DeepSeek-R1-Distill-Qwen-7B-GGUF/internlm_OREAL-DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf
- &qwen2 - &qwen2
url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## Start QWEN2 url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## Start QWEN2
name: "qwen2-7b-instruct" name: "qwen2-7b-instruct"