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README.md
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---
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license: bigscience-bloom-rail-1.0
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language:
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- ak
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- ar
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- as
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- bm
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- bn
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- ca
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- code
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- en
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- es
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- eu
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- fon
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- fr
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- gu
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- hi
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- id
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- ig
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- ki
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- kn
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- lg
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- ln
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- ml
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- mr
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- ne
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- nso
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- ny
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- or
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- pa
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- pt
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- rn
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- rw
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- sn
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- st
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- sw
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- ta
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- te
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- tn
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- ts
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- tum
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- tw
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- ur
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- vi
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- wo
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- xh
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- yo
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- zh
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- zhs
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- zht
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- zu
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pipeline_tag: text-generation
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tags:
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- llama-cpp
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- gguf-my-repo
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base_model: bigscience/bloom-560m
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---
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# fernandoruiz/bloom-560m-Q4_0-GGUF
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This model was converted to GGUF format from [`bigscience/bloom-560m`](https://huggingface.co/bigscience/bloom-560m) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/bigscience/bloom-560m) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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llama-cli --hf-repo fernandoruiz/bloom-560m-Q4_0-GGUF --hf-file bloom-560m-q4_0.gguf -p "The meaning to life and the universe is"
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```
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### Server:
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```bash
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llama-server --hf-repo fernandoruiz/bloom-560m-Q4_0-GGUF --hf-file bloom-560m-q4_0.gguf -c 2048
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```
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo fernandoruiz/bloom-560m-Q4_0-GGUF --hf-file bloom-560m-q4_0.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo fernandoruiz/bloom-560m-Q4_0-GGUF --hf-file bloom-560m-q4_0.gguf -c 2048
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```
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