--- base_model: rombodawg/Rombos-Coder-V2.5-Qwen-7b tags: - llama-cpp - gguf-my-repo - cline --- # benhaotang/Rombos-Coder-V2.5-Qwen-7b-Q8_0-GGUF This model was converted to GGUF format from [`rombodawg/Rombos-Coder-V2.5-Qwen-7b`](https://huggingface.co/rombodawg/Rombos-Coder-V2.5-Qwen-7b) 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/rombodawg/Rombos-Coder-V2.5-Qwen-7b) for more details on the model. ## Use with Cline and Ollama use this template file from https://github.com/maryasov/ollama-models-instruct-for-cline ``` FROM rombos-coder-v2.5-qwen-7b-q8_0.gguf TEMPLATE """{{- /* Initial system message with core instructions */ -}} {{- if .Messages }} {{- if or .System .Tools }} <|im_start|>system {{- if .System }} {{ .System }} {{- end }} {{- if .Tools }} # Tools and XML Schema You have access to the following tools. Each tool must be used according to this XML schema: {{- range .Tools }} {{ .Function }} {{- end }} ## Tool Use Format 1. Think about the approach in tags 2. Call tool using XML format: value 3. Process tool response from: result {{- end }} <|im_end|> {{- end }} {{- /* Message handling loop */ -}} {{- range $i, $_ := .Messages }} {{- $last := eq (len (slice $.Messages $i)) 1 }} {{- /* User messages */ -}} {{- if eq .Role "user" }} <|im_start|>user {{ .Content }} <|im_end|> {{- /* Assistant messages */ -}} {{- else if eq .Role "assistant" }} <|im_start|>assistant {{- if .Content }} {{ .Content }} {{- else if .ToolCalls }} {{- range .ToolCalls }} [Analysis of current state and next steps] <{{ .Function.Name }}> {{- range $key, $value := .Function.Arguments }} <{{ $key }}>{{ $value }} {{- end }} {{- end }} {{- end }} {{- if not $last }}<|im_end|>{{- end }} {{- /* Tool response handling */ -}} {{- else if eq .Role "tool" }} <|im_start|>user {{ .Content }} <|im_end|> {{- end }} {{- /* Prepare for next assistant response if needed */ -}} {{- if and (ne .Role "assistant") $last }} <|im_start|>assistant {{- end }} {{- end }} {{- /* Handle single message case */ -}} {{- else }} {{- if .System }} <|im_start|>system {{ .System }} <|im_end|> {{- end }} {{- if .Prompt }} <|im_start|>user {{ .Prompt }} <|im_end|> {{- end }} <|im_start|>assistant {{- end }} {{ .Response }} {{- if .Response }}<|im_end|>{{- end }} """ PARAMETER repeat_last_n 64 PARAMETER repeat_penalty 1.1 PARAMETER stop "<|im_start|>" PARAMETER stop "<|im_end|>" PARAMETER stop "<|endoftext|>" PARAMETER temperature 0.1 PARAMETER top_k 40 PARAMETER top_p 0.9 ``` ## 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 benhaotang/Rombos-Coder-V2.5-Qwen-7b-Q8_0-GGUF --hf-file rombos-coder-v2.5-qwen-7b-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo benhaotang/Rombos-Coder-V2.5-Qwen-7b-Q8_0-GGUF --hf-file rombos-coder-v2.5-qwen-7b-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 benhaotang/Rombos-Coder-V2.5-Qwen-7b-Q8_0-GGUF --hf-file rombos-coder-v2.5-qwen-7b-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo benhaotang/Rombos-Coder-V2.5-Qwen-7b-Q8_0-GGUF --hf-file rombos-coder-v2.5-qwen-7b-q8_0.gguf -c 2048 ```