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Browse files- .dockerignore +1 -0
- Dockerfile +14 -3
.dockerignore
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token.txt
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Dockerfile
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# Base Image
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FROM python:3.10-slim
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1
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WORKDIR /code
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@@ -43,8 +47,15 @@ RUN python -c "from transformers import pipeline; pipeline('text-to-speech', mod
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&& python -c "from transformers import pipeline; pipeline('text-to-speech', model='facebook/mms-tts-yor')"
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# Pre-load N-ATLaS model during build
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RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/N-ATLaS')" \
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&& python -c "from transformers import AutoTokenizer, AutoModelForCausalLM; import torch; tokenizer = AutoTokenizer.from_pretrained('NCAIR1/N-ATLaS'); model = AutoModelForCausalLM.from_pretrained('NCAIR1/N-ATLaS', torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32, device_map='auto' if torch.cuda.is_available() else None, trust_remote_code=True, low_cpu_mem_usage=True, use_cache=True); print('N-ATLaS model loaded successfully')"
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# Copy project files
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COPY . .
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# Base Image
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FROM python:3.10-slim
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# Build argument for Hugging Face token
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ARG HF_TOKEN
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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HF_TOKEN=${HF_TOKEN}
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WORKDIR /code
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&& python -c "from transformers import pipeline; pipeline('text-to-speech', model='facebook/mms-tts-yor')"
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# Pre-load N-ATLaS model during build
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RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/N-ATLaS', token='$HF_TOKEN')" \
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&& python -c "from transformers import AutoTokenizer, AutoModelForCausalLM; import torch; tokenizer = AutoTokenizer.from_pretrained('NCAIR1/N-ATLaS', token='$HF_TOKEN'); model = AutoModelForCausalLM.from_pretrained('NCAIR1/N-ATLaS', torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32, device_map='auto' if torch.cuda.is_available() else None, trust_remote_code=True, low_cpu_mem_usage=True, use_cache=True, token='$HF_TOKEN'); print('N-ATLaS model loaded successfully')"
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# Pre-download ASR models (will be lazy-loaded at runtime)
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RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/Hausa-ASR', token='$HF_TOKEN')" \
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&& python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/Yoruba-ASR', token='$HF_TOKEN')" \
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&& python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/Igbo-ASR', token='$HF_TOKEN')" \
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&& python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='NCAIR1/NigerianAccentedEnglish', token='$HF_TOKEN')" \
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&& find /models/huggingface -name '*.lock' -delete
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# Copy project files
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COPY . .
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