Skip to content
ModelListedExternal
Download

TimeLens 8B Q4 0 GGUF

bsd-3-clause

KindOtherBase modelTencentARC/TimeLens-8BVersionTimelens 8b q4 0Cgrade

Model source

Kind
Other
File size
4.45 GB
Base model
TencentARC/TimeLens-8B
Version
vTimelens 8b q4 0
Updated
Oct 20, 2026
Source
Hugging Face

Source description

introvoyz041/TimeLens-8B-Q4_0-GGUF

This model was converted to GGUF format from TencentARC/TimeLens-8B 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 introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-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 introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -c 2048

Sources

1 source
Hugging FacePrimaryVersion 10f99e8d7278d6be314c803b74beba6aa0fe0ad4
huggingface.co/introvoyz041/TimeLens-8B-Q4_0-GGUF/tree/10f99e8d7278d6be314c803b74beba6aa0fe0ad4

Verified Aug 6

Model artifacts

1 artifact

timelens-8b-q4_0.gguf

gguf · 4.45 GB · SHA-256 8d05bf3a7be6…19b2 · Hugging Face

Download

Source excerpts

2 excerpts

--- license: other license_name: bsd-3-clause license_link: https://github.com/TencentARC/TimeLens/blob/main/LICENSE language: - en tags: - video-grounding - temporal-grounding - video-understanding - qwen3-vl - llama-cpp - gguf-my-repo library_name: transformers pipeline_tag: video-text-to-text datasets: - TencentARC/TimeLens-100K - TencentARC/TimeLens-Bench base_model: TencentARC/TimeLens-8B --- # introvoyz041/TimeLens-8B-Q4_0-GGUF This model was converted to GGUF format from [`TencentARC/TimeLens-8B`](https://huggingface.co/TencentARC/TimeLens-8B) 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/TencentARC/TimeLens-8B) 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 introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-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 introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo introvoyz041/TimeLens-8B-Q4_0-GGUF --hf-file timelens-8b-q4_0.gguf -c 2048 ```

Source context: 17 downloads · 0 likes · Pipeline video-text-to-text · Library transformers · Repo introvoyz041/TimeLens-8B-Q4_0-GGUF