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+1
-1
@@ -13,7 +13,7 @@ However, this will cause every worker to download the model from the Hugging Fac
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A naive way to cache the model would be to store it on a network volume in RunPod and reference the model files this way:
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A naive way to cache the model would be to store it on a network volume in RunPod and reference the model files this way:
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```bash
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```bash
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-hf /runpod-volume/model.gguf --ctx-size 4096 # etc...
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-m /runpod-volume/model.gguf --ctx-size 4096 # etc...
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```
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```
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Unfortunately, network volume performance is often not sufficient for loading large models, leading to long load times. RunPod introduced a [caching mechanism](https://docs.runpod.io/serverless/endpoints/model-caching) to solve this problem.
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Unfortunately, network volume performance is often not sufficient for loading large models, leading to long load times. RunPod introduced a [caching mechanism](https://docs.runpod.io/serverless/endpoints/model-caching) to solve this problem.
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+8
-1
@@ -3,6 +3,7 @@ Finds the full LLM GGUF path from the Hugging Face cache.
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"""
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"""
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import os
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import os
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import sys
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import argparse
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import argparse
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CACHE_DIR = "/runpod-volume/huggingface-cache/hub"
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CACHE_DIR = "/runpod-volume/huggingface-cache/hub"
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@@ -19,7 +20,7 @@ def find_model_path(model_name, gguf_in_repo="model.gguf"):
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The full path to the cached model, or None if not found
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The full path to the cached model, or None if not found
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"""
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"""
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cache_name = model_name.replace("/", "--")
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cache_name = model_name.replace("/", "--").lower()
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snapshots_dir = os.path.join(
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snapshots_dir = os.path.join(
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CACHE_DIR, f"models--{cache_name}", "snapshots"
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CACHE_DIR, f"models--{cache_name}", "snapshots"
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)
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)
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@@ -52,6 +53,12 @@ def main():
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args = parser.parse_args()
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args = parser.parse_args()
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model_path = find_model_path(args.model, args.path)
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model_path = find_model_path(args.model, args.path)
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if model_path is None:
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print(
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f"Error: Cached model not found. Model='{args.model}', GGUF='{args.path}', Cache dir='{CACHE_DIR}'",
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file=sys.stderr,
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)
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sys.exit(1)
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print(model_path, end="")
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print(model_path, end="")
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+7
-1
@@ -17,7 +17,13 @@ cleanup() {
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CACHED_LLAMA_ARGS=""
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CACHED_LLAMA_ARGS=""
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find_cached_path() {
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find_cached_path() {
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CACHED_LLAMA_ARGS="-m $(python ./find_cached.py $LLAMA_CACHED_MODEL $LLAMA_CACHED_GGUF_PATH)"
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local model_path
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model_path=$(python ./find_cached.py "$LLAMA_CACHED_MODEL" "$LLAMA_CACHED_GGUF_PATH")
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if [ $? -ne 0 ] || [ -z "$model_path" ]; then
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echo "start.sh: Error: Could not resolve cached model path. Check that LLAMA_CACHED_MODEL and LLAMA_CACHED_GGUF_PATH are correct and the model is fully cached on the network volume."
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exit 1
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fi
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CACHED_LLAMA_ARGS="-m $model_path"
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}
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}
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# check if $LLAMA_CACHED_MODEL is set and not empty
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# check if $LLAMA_CACHED_MODEL is set and not empty
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