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Build error
Build error
base model in config is unnecessary, and fix grammar
Browse files- chat.py +1 -1
- config.yml +0 -2
chat.py
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@@ -86,7 +86,7 @@ with blocks:
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gr.Markdown(f"""
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### brought to you by OpenAccess AI Collective
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- This is the [{config["repo"]}](https://huggingface.co/{config["repo"]}) model file [{config["file"]}](https://huggingface.co/{config["repo"]}/blob/main/{config["file"]})
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- This Space uses GGML with GPU support, so it can run larger models on smaller GPUs & VRAM
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- This is running on a smaller, shared GPU, so it may take a few seconds to respond.
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- [Duplicate the Space](https://huggingface.co/spaces/openaccess-ai-collective/ggml-ui?duplicate=true) to skip the queue and run in a private space or to use your own GGML models.
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- When using your own models, simply update the [config.yml](https://huggingface.co/spaces/openaccess-ai-collective/ggml-ui/blob/main/config.yml)")
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gr.Markdown(f"""
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### brought to you by OpenAccess AI Collective
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- This is the [{config["repo"]}](https://huggingface.co/{config["repo"]}) model file [{config["file"]}](https://huggingface.co/{config["repo"]}/blob/main/{config["file"]})
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+
- This Space uses GGML with GPU support, so it can quickly run larger models on smaller GPUs & VRAM.
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- This is running on a smaller, shared GPU, so it may take a few seconds to respond.
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- [Duplicate the Space](https://huggingface.co/spaces/openaccess-ai-collective/ggml-ui?duplicate=true) to skip the queue and run in a private space or to use your own GGML models.
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- When using your own models, simply update the [config.yml](https://huggingface.co/spaces/openaccess-ai-collective/ggml-ui/blob/main/config.yml)")
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config.yml
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@@ -1,8 +1,6 @@
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---
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repo: TheBloke/wizard-vicuna-13B-GGML
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file: wizard-vicuna-13B.ggml.q5_1.bin
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# if the repo above doesn't include the tokenizer set the base repo it was based on with a valid tokenizer model
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base_model: junelee/wizard-vicuna-13b
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llama_cpp:
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n_ctx: 2048
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n_gpu_layers: 40 # llama 13b has 40 layers
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---
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repo: TheBloke/wizard-vicuna-13B-GGML
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file: wizard-vicuna-13B.ggml.q5_1.bin
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llama_cpp:
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n_ctx: 2048
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n_gpu_layers: 40 # llama 13b has 40 layers
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