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HumanFlow Q4 0 GGUF

This model was converted to GGUF format from randhir302/HumanFlow using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

ArtCheckpointBasismodellrandhir302/HumanFlowVersionRevision 734b317Verleger@randhir302CBewertung

Modellquelle

Art
Checkpoint
Dateigröße
4,34 GB
Basismodell
randhir302/HumanFlow
Version
vRevision 734b317
Aktualisiert
1. Okt. 2026
Verleger
@randhir302
Downloads
22
Aufgaben
Textgenerierung
Quelle
Hugging Face

Quellenbeschreibung

randhir302/HumanFlow-Q4_0-GGUF

This model was converted to GGUF format from randhir302/HumanFlow using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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 randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -c 2048

Quellen

1 Quelle
Hugging FacePrimärVersion 734b3171ae45357390e33e9b71b0cfe9ce9ff4e7
huggingface.co/randhir302/HumanFlow-Q4_0-GGUF/tree/734b3171ae45357390e33e9b71b0cfe9ce9ff4e7

Verifiziert 1. Okt.

Modellartefakte

1 Artefakt

humanflow-q4_0.gguf

gguf · 4,34 GB · SHA-256 ab04f62d0bf5…9467 · Hugging Face

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Quellenauszüge

3 Auszüge

--- language: - en license: apache-2.0 base_model: randhir302/HumanFlow library_name: transformers pipeline_tag: text-generation tags: - text-generation - llama3 - humanizer - rewriting - conversational - merged - sft - editorial - llama-cpp - gguf-my-repo widget: - text: 'Rewrite this in a more human tone: The system is functioning correctly.' example_title: Smooth System - text: 'Rewrite this in a more human tone: The implementation has been completed successfully.' example_title: Successful Setup - text: 'Rewrite this in a more human tone: The user is advised to proceed with caution.' example_title: Friendly Warning model-index: - name: HumanFlow-Llama3-8B results: - task: type: text-generation dataset: name: Internal Evaluation Suite type: custom metrics: - type: BERTScore F1 value: 0.8424 - type: ROUGE-L value: 0.0908 - type: Perplexity value: 1.5242 - type: Text Overlap value: 0.0528 --- # randhir302/HumanFlow-Q4_0-GGUF This model was converted to GGUF format from [`randhir302/HumanFlow`](https://huggingface.co/randhir302/HumanFlow) 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/randhir302/HumanFlow) 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 randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_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 randhir302/HumanFlow-Q4_0-GGUF --hf-file humanflow-q4_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama...

Source context: 22 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo randhir302/HumanFlow-Q4_0-GGUF

Source context: 3 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo randhir302/HumanFlow-Q4_0-GGUF