Instructions to use prithivMLmods/TimeLens-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/TimeLens-8B-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="prithivMLmods/TimeLens-8B-GGUF")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("prithivMLmods/TimeLens-8B-GGUF", dtype="auto")

llama-cpp-python

How to use prithivMLmods/TimeLens-8B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="prithivMLmods/TimeLens-8B-GGUF",
	filename="TimeLens-8B.IQ4_XS.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "Describe this image in one sentence."
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use prithivMLmods/TimeLens-8B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use prithivMLmods/TimeLens-8B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prithivMLmods/TimeLens-8B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/TimeLens-8B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

SGLang

How to use prithivMLmods/TimeLens-8B-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "prithivMLmods/TimeLens-8B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/TimeLens-8B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "prithivMLmods/TimeLens-8B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/TimeLens-8B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Ollama
How to use prithivMLmods/TimeLens-8B-GGUF with Ollama:
```
ollama run hf.co/prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
```

Unsloth Studio

How to use prithivMLmods/TimeLens-8B-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for prithivMLmods/TimeLens-8B-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for prithivMLmods/TimeLens-8B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for prithivMLmods/TimeLens-8B-GGUF to start chatting

How to use prithivMLmods/TimeLens-8B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "prithivMLmods/TimeLens-8B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use prithivMLmods/TimeLens-8B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use prithivMLmods/TimeLens-8B-GGUF with Docker Model Runner:
```
docker model run hf.co/prithivMLmods/TimeLens-8B-GGUF:Q4_K_M
```

Lemonade

How to use prithivMLmods/TimeLens-8B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull prithivMLmods/TimeLens-8B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.TimeLens-8B-GGUF-Q4_K_M

List all available models

lemonade list

@@ -33,3 +33,17 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.f16.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.mmproj-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+TimeLens-8B.mmproj-f16.gguf filter=lfs diff=lfs merge=lfs -text

prithivMLmods
/

TimeLens-8B-GGUF

Upload folder using huggingface_hub

+version https://git-lfs.github.com/spec/v1
+oid sha256:f84f0448826c745085158e79804e63b7a530c5c57edf9ddfb0551b69c34473b1
+size 4593299104

+version https://git-lfs.github.com/spec/v1
+oid sha256:0f78607c5baea20c4aa98587b1e76c0c21f5b502b869e7106a8fa8d29c0920da
+size 3281735328

+version https://git-lfs.github.com/spec/v1
+oid sha256:201f6ce5b4462f9191d3df13e17c63e5204b03a558c0e3d92a4ca12608235a39
+size 4431396512

+version https://git-lfs.github.com/spec/v1
+oid sha256:80dc9bb1fa133d017d455992b2d48504a1ecfac7f540d353c9cc791f84324a8a
+size 4124163744

+version https://git-lfs.github.com/spec/v1
+oid sha256:57d090956f2016f43081b1062c7263aff48df77e30ffe5ea05ed64d0e4ae230e
+size 3769613984

+version https://git-lfs.github.com/spec/v1
+oid sha256:35a64b7ebb1926cf0162a604ceb78921118c21cf9474dbc797601b22c7c28ee6
+size 5027786400

+version https://git-lfs.github.com/spec/v1
+oid sha256:10161a5303a16fe6ec69823678cdce77c1e6a8e670ae32dc64174214e7e551e2
+size 4802014880

+version https://git-lfs.github.com/spec/v1
+oid sha256:8b90ac0063db4c1b01a5d4f3e6494fbf3cb9499c4cc030f3d29f3eacd6c2444c
+size 5851115168

+version https://git-lfs.github.com/spec/v1
+oid sha256:eab3890bbcda97492d88fbf1fad31d2ec7fcd44d539a181d4a8932939317788f
+size 5720764064

+version https://git-lfs.github.com/spec/v1
+oid sha256:0987df7e1b4759b74e0a89390ddc20b97cff8aaf200f91edff9d5cda25983c2b
+size 6725901984

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:20abe90426ccc289be8d813cad0fe88654b9fdaeea488fdd5d2cd18720f8a18f
+size 8709521056

+version https://git-lfs.github.com/spec/v1
+oid sha256:45ee2e3d129b211b0f9fd80b75e19000648cd12660a59071e382525ea8da0c18
+size 16388046496

+version https://git-lfs.github.com/spec/v1
+oid sha256:1962cd9adb92a0553962545f6d713ee68586cb49a611ea5a6ae1b6b155d73c5b
+size 752290944

+version https://git-lfs.github.com/spec/v1
+oid sha256:f1a89135dbaa94b91fce0fe934fb34f2d6c61a7c5157f5a49d5694dc90f521cc
+size 1159031040