Instructions to use ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ling1000T/John1604-HIPAA-English-gguf:Q4_K_M

Use Docker

docker model run hf.co/ling1000T/John1604-HIPAA-English-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use ling1000T/John1604-HIPAA-English-gguf with Ollama:
```
ollama run hf.co/ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
```
Unsloth Desktop

How to use ling1000T/John1604-HIPAA-English-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ling1000T/John1604-HIPAA-English-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": "ling1000T/John1604-HIPAA-English-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ling1000T/John1604-HIPAA-English-gguf with Docker Model Runner:
```
docker model run hf.co/ling1000T/John1604-HIPAA-English-gguf:Q4_K_M
```

Lemonade

How to use ling1000T/John1604-HIPAA-English-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ling1000T/John1604-HIPAA-English-gguf:Q4_K_M

Run and chat with the model

lemonade run user.John1604-HIPAA-English-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-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 ling1000T/John1604-HIPAA-English-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ling1000T/John1604-HIPAA-English-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ling1000T/John1604-HIPAA-English-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 "ling1000T/John1604-HIPAA-English-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"

John1604's LLM for HIPAA

LLM for HIPAA

This is the LLM about HIPPA law. Ask the LLM about HIPAA. It runs in both ollama and LM studio.

Use the model in ollama

First download and install ollama.

https://ollama.com/download

Command

in windows command line, or in terminal in ubuntu, type:

ollama run hf.co/ling1000T/John1604-HIPAA-English-gguf:q6_k

(q6_k is the model quant type, q5_k_s, q4_k_m, ..., can also be used)

C:\Users\developer>ollama run hf.co/ling1000T/John1604-HIPAA-English-gguf:q6_k
pulling manifest
...
verifying sha256 digest
writing manifest
success

>>> in a form authorization, patient was asked to provide agreement
to let other third parties and provider to share patient information.
can patient refuse?

Yes, a patient has the right to refuse in a form authorization. Even though
some commenters suggested that patients might be confused about what they are agreeing to,
there is no indication that this confusion would lead patients to sign
authorizations without understanding or consent. The current rule allows
for conditional authorizations when the condition is clearly indicated—such
as requiring payment before treatment—but the Department maintains
that this standard should not be expanded in a way that undermines patient autonomy.
Therefore, patients retain control over their health information and can choose
not to agree to the sharing of their information with other third parties or providers.

>>> Send a message (/? for help)

After you run command: ollama run hf.co/ling1000T/John1604-HIPAA-English-gguf:q6_k, it will appear in ollama UI - you may select this model hf.co/ling1000T/John1604-HIPAA-English-gguf:q6_k from the model list, and run it the same way as other ollama pre-configured models.

Use the model in LM Studio

download and install LM Studio

https://lmstudio.ai/

Discover models

In the LM Studio, click "Discover" icon. "Mission Control" popup window will be displayed.

In the "Mission Control" search bar, type "ling1000T/John1604-HIPAA-English-gguf" and check "GGUF", the model should be found.

Download the model.

Load the model.

Ask questions.

quantized models

Type	Bits	Quality	Description
Q2_K	2-bit	🟥 Low	Minimal footprint; only for tests
Q3_K_S	3-bit	🟧 Low	“Small” variant (less accurate)
Q3_K_M	3-bit	🟧 Low–Med	“Medium” variant
Q4_K_S	4-bit	🟨 Med	Small, faster, slightly less quality
Q4_K_M	4-bit	🟩 Med–High	“Medium” — best 4-bit balance
Q5_K_S	5-bit	🟩 High	Slightly smaller than Q5_K_M
Q5_K_M	5-bit	🟩🟩 High	Excellent general-purpose quant
Q6_K	6-bit	🟩🟩🟩 Very High	Almost FP16 quality, larger size
Q8_0	8-bit	🟩🟩🟩🟩	Near-lossless baseline
F16	16-bit	🟩🟩🟩🟩	baseline

International Inventor's License

If the use is not commercial, it is free to use without any fees.

For commercial use, if the company or individual does not make any profit, no fees are required.

For commercial use, if the company or individual has a net profit, they should pay 1% of the net profit or 0.5% of the sales revenue, whichever is less.

For commercial use, we provide product-related services.

Downloads last month: 46

GGUF

Model size

8B params

Architecture

qwen3

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for ling1000T/John1604-HIPAA-English-gguf

Base model

Qwen/Qwen3-8B-Base

Finetuned

Qwen/Qwen3-8B

Finetuned

John1604/John1604-AML3-HYPAA-English

Quantized

(2)

this model