Update README.md

README.md

@@ -1,58 +1,14 @@
 ---
-base_model: appvoid/graphite-001-medium-v4
 library_name: transformers
 tags:
 - text-generation
 - text-editing
 - rewriting
 - paraphrasing
-- falcon-h1
 - instruct
 - llama-cpp
-- gguf-my-repo
 private: true
 ---
 
-# appvoid/graphite-001-medium-v4-Q8_0-GGUF
-This model was converted to GGUF format from [`appvoid/graphite-001-medium-v4`](https://huggingface.co/appvoid/graphite-001-medium-v4) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/appvoid/graphite-001-medium-v4) for more details on the model.
-
-## Use with llama.cpp
-Install llama.cpp through brew (works on Mac and Linux)
-
-```bash
-brew install llama.cpp
-
-```
-Invoke the llama.cpp server or the CLI.
-
-### CLI:
-```bash
-llama-cli --hf-repo appvoid/graphite-001-medium-v4-Q8_0-GGUF --hf-file graphite-001-medium-v4-q8_0.gguf -p "The meaning to life and the universe is"
-```
-
-### Server:
-```bash
-llama-server --hf-repo appvoid/graphite-001-medium-v4-Q8_0-GGUF --hf-file graphite-001-medium-v4-q8_0.gguf -c 2048
-```
-
-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.
-
-Step 1: Clone llama.cpp from GitHub.
-```
-git clone https://github.com/ggerganov/llama.cpp
-```
-
-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).
-```
-cd llama.cpp && LLAMA_CURL=1 make
-```
-
-Step 3: Run inference through the main binary.
-```
-./llama-cli --hf-repo appvoid/graphite-001-medium-v4-Q8_0-GGUF --hf-file graphite-001-medium-v4-q8_0.gguf -p "The meaning to life and the universe is"
-```
-or
-```
-./llama-server --hf-repo appvoid/graphite-001-medium-v4-Q8_0-GGUF --hf-file graphite-001-medium-v4-q8_0.gguf -c 2048
-```
+# carbono
+This is a model trained on a diverse set of instruction tasks to make LFM2.5 work on production environments.