Transformers
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falcon
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@@ -25,9 +25,12 @@ license: apache-2.0
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  These files are **experimental** GGML format model files for [Falcon 7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct).
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- These GGML files will **not** work in llama.cpp, and at the time of writing they will not work with any UI or library. They cannot be used from Python code.
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- They can be used with a new fork of llama.cpp that adds Falcon GGML support: [cmp-nc/ggllm.cpp](https://github.com/cmp-nct/ggllm.cpp)
 
 
 
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  Note: It is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.
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@@ -40,7 +43,11 @@ Note: It is not currently possible to use the new k-quant formats with Falcon 7B
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  <!-- compatibility_ggml start -->
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  ## Compatibility
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- To build cmp-nct's fork of llama.cpp with Falcon 7B support plus preliminary CUDA acceleration, please try the following steps:
 
 
 
 
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  ```
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  git clone https://github.com/cmp-nct/ggllm.cpp
 
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  These files are **experimental** GGML format model files for [Falcon 7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct).
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+ These GGML files will **not** work in llama.cpp, text-generation-webui or KoboldCpp.
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+ They can be used from:
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+ * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui).
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+ * The ctransformers Python library, which includes LangChain support: [ctransformers](https://github.com/marella/ctransformers).
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+ * A new fork of llama.cpp that introduced this new Falcon GGML support: [cmp-nc/ggllm.cpp](https://github.com/cmp-nct/ggllm.cpp).
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  Note: It is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.
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  <!-- compatibility_ggml start -->
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  ## Compatibility
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+ The recommended UI for these GGMLs is [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui). Preliminary CUDA GPU acceleration is provided.
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+ For use from Python code, use [ctransformers](https://github.com/marella/ctransformers). Again, with preliminary CUDA GPU acceleration
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+ Or to build cmp-nct's fork of llama.cpp with Falcon 7B support plus preliminary CUDA acceleration, please try the following steps:
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  ```
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  git clone https://github.com/cmp-nct/ggllm.cpp