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mzbac/CodeLlama-34b-guanaco-awq
CodeLlama-34b-guanaco-awq is a text generation model from mzbac. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Codellama 34b base model fine-tuned on the text chunk from the OpenAssistant-Guanaco dataset instead of Q&A pair, so it struggles to determine the end of the answer. recommend using a stop string like " Human:" to pre…
Downloads · 30 days
26
11% of all-time downloads
All-time downloads
237
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33.7B
18.3 GB on disk
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How the weights are stored.
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From the Hugging Face model README
Codellama 34b base model fine-tuned on the text chunk from the OpenAssistant-Guanaco dataset instead of Q&A pair, so it struggles to determine the end of the answer. recommend using a stop string like "### Human:" to prevent the model from talking to itself.
Prompt template:
### Human: {prompt}
### Assistant:
Run the model via text-generation-inference
One GPU:
sudo docker run --gpus all --shm-size 1g -p 5000:80 -v $PWD/models:/data ghcr.io/huggingface/text-generation-inference:latest --max-total-tokens 4096 --quantize awq --model-id mzbac/CodeLlama-34b-guanaco-awq
Two GPUs:
docker run --gpus all --shm-size 1g -p 5000:80 -v $PWD/models:/data ghcr.io/huggingface/text-generation-inference:latest --max-total-tokens 4096 --max-input-length 4000 --max-batch-prefill-tokens 4096 --quantize awq --num-shard 2 --model-id mzbac/CodeLlama-34b-guanaco-awq
Query the mode via curl
curl 127.0.0.1:8001/generate \
-X POST \
-d '{"inputs":"### Human: 给我准备一个去日本旅行的计划\n### Assistant:", "parameters":{"max_new_tokens":2048, "stop": [
"### Human:"
]}}' \
-H 'Content-Type: application/json'