Instructions to use nicolasembleton/context-1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use nicolasembleton/context-1-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf nicolasembleton/context-1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nicolasembleton/context-1-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf nicolasembleton/context-1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nicolasembleton/context-1-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 nicolasembleton/context-1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf nicolasembleton/context-1-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 nicolasembleton/context-1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nicolasembleton/context-1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/nicolasembleton/context-1-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use nicolasembleton/context-1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nicolasembleton/context-1-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": "nicolasembleton/context-1-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nicolasembleton/context-1-GGUF:Q4_K_M

Ollama
How to use nicolasembleton/context-1-GGUF with Ollama:
```
ollama run hf.co/nicolasembleton/context-1-GGUF:Q4_K_M
```

Unsloth Studio

How to use nicolasembleton/context-1-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 nicolasembleton/context-1-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 nicolasembleton/context-1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for nicolasembleton/context-1-GGUF to start chatting

How to use nicolasembleton/context-1-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nicolasembleton/context-1-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "nicolasembleton/context-1-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use nicolasembleton/context-1-GGUF with Docker Model Runner:
```
docker model run hf.co/nicolasembleton/context-1-GGUF:Q4_K_M
```

Lemonade

How to use nicolasembleton/context-1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nicolasembleton/context-1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.context-1-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use nicolasembleton/context-1-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nicolasembleton/context-1-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 nicolasembleton/context-1-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use nicolasembleton/context-1-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf nicolasembleton/context-1-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "nicolasembleton/context-1-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

nicolasembleton commited on Mar 28

Commit

f485ca9

verified ·

1 Parent(s): fe43437

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +6 -18

README.md CHANGED Viewed

@@ -30,23 +30,17 @@ GGUF quantized versions of [chromadb/context-1](https://huggingface.co/chromadb/
 | **Hidden Size** | 2880 |
 | **License** | Apache-2.0 |
-## Quantization Details
-Quantized from the F16 safetensors in the original repository using [llama.cpp](https://github.com/ggml-org/llama.cpp)'s `llama-quantize` tool, running on NVIDIA H100 via [Modal](https://modal.com/).
-| File | Format | Size |
-|------|--------|------|
-| `context-1-Q4_K_M.gguf` | Q4_K_M | 15.81 GB |
-More quantization levels (Q3, Q5, Q8, etc.) may be added in the future.
 ## Usage
 ### llama.cpp
 ```bash
-# Download
-huggingface-cli download nicoism/context-1-GGUF context-1-Q4_K_M.gguf --local-dir .
 # Run
 ./llama-cli -m context-1-Q4_K_M.gguf -p "Your prompt here" -ngl 99
@@ -54,7 +48,7 @@ huggingface-cli download nicoism/context-1-GGUF context-1-Q4_K_M.gguf --local-di
 ### LM Studio
-Search for `nicoism/context-1-GGUF` in LM Studio's model browser and download the desired quantization.
 ### Python (llama-cpp-python)
@@ -62,7 +56,7 @@ Search for `nicoism/context-1-GGUF` in LM Studio's model browser and download th
 from llama_cpp import Llama
 llm = Llama.from_pretrained(
-    repo_id="nicoism/context-1-GGUF",
     filename="context-1-Q4_K_M.gguf",
     n_gpu_layers=-1,
 )
@@ -88,12 +82,6 @@ Format overview:
 For the full template, see [`chat_template.jinja`](https://huggingface.co/chromadb/context-1/blob/main/chat_template.jinja) in the original repository.
-## Limitations
-- GGUF quantization introduces minor quality degradation compared to the original F16 weights. Q4_K_M provides a good balance of quality and size.
-- This model inherits any biases and limitations from the base model.
-- Requires a GPU or sufficient RAM for inference (16 GB+ for Q4_K_M).
 ## License
 Apache-2.0 — same as the [original model](https://huggingface.co/chromadb/context-1).

 | **Hidden Size** | 2880 |
 | **License** | Apache-2.0 |
+## Quantization
+Quantized from F16 weights using [llama.cpp](https://github.com/ggml-org/llama.cpp) with importance matrix (imatrix) calibration, running on NVIDIA H100 GPUs via [Modal](https://modal.com/). All standard K-quant and I-quant variants are provided.
 ## Usage
 ### llama.cpp
 ```bash
+# Download your preferred quant
+huggingface-cli download nicolasembleton/context-1-GGUF context-1-Q4_K_M.gguf --local-dir .
 # Run
 ./llama-cli -m context-1-Q4_K_M.gguf -p "Your prompt here" -ngl 99
 ### LM Studio
+Search for `nicolasembleton/context-1-GGUF` in LM Studio's model browser and download the desired quantization.
 ### Python (llama-cpp-python)
 from llama_cpp import Llama
 llm = Llama.from_pretrained(
+    repo_id="nicolasembleton/context-1-GGUF",
     filename="context-1-Q4_K_M.gguf",
     n_gpu_layers=-1,
 )
 For the full template, see [`chat_template.jinja`](https://huggingface.co/chromadb/context-1/blob/main/chat_template.jinja) in the original repository.
 ## License
 Apache-2.0 — same as the [original model](https://huggingface.co/chromadb/context-1).