Instructions to use miketeod/Llama-patentLLMClaimsSmall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use miketeod/Llama-patentLLMClaimsSmall 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 miketeod/Llama-patentLLMClaimsSmall:Q8_0
# Run inference directly in the terminal:
llama cli -hf miketeod/Llama-patentLLMClaimsSmall:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf miketeod/Llama-patentLLMClaimsSmall:Q8_0
# Run inference directly in the terminal:
llama cli -hf miketeod/Llama-patentLLMClaimsSmall:Q8_0

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 miketeod/Llama-patentLLMClaimsSmall:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf miketeod/Llama-patentLLMClaimsSmall:Q8_0

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 miketeod/Llama-patentLLMClaimsSmall:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf miketeod/Llama-patentLLMClaimsSmall:Q8_0

Use Docker

docker model run hf.co/miketeod/Llama-patentLLMClaimsSmall:Q8_0

LM Studio
Jan

vLLM

How to use miketeod/Llama-patentLLMClaimsSmall with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "miketeod/Llama-patentLLMClaimsSmall"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "miketeod/Llama-patentLLMClaimsSmall",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/miketeod/Llama-patentLLMClaimsSmall:Q8_0

Ollama
How to use miketeod/Llama-patentLLMClaimsSmall with Ollama:
```
ollama run hf.co/miketeod/Llama-patentLLMClaimsSmall:Q8_0
```

Unsloth Studio

How to use miketeod/Llama-patentLLMClaimsSmall 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 miketeod/Llama-patentLLMClaimsSmall 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 miketeod/Llama-patentLLMClaimsSmall to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for miketeod/Llama-patentLLMClaimsSmall to start chatting

Docker Model Runner
How to use miketeod/Llama-patentLLMClaimsSmall with Docker Model Runner:
```
docker model run hf.co/miketeod/Llama-patentLLMClaimsSmall:Q8_0
```

Lemonade

How to use miketeod/Llama-patentLLMClaimsSmall with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull miketeod/Llama-patentLLMClaimsSmall:Q8_0

Run and chat with the model

lemonade run user.Llama-patentLLMClaimsSmall-Q8_0

List all available models

lemonade list

Atomic Chat

Llama-patentLLMClaimsSmall

Built with Llama.

Pilot-scale fine-tune of Llama-3.1-8B-Instruct for US utility patent claim drafting: given a detailed description, generate the full claim set (and the reverse: specification from a brief summary).

Training: 45,000 examples uniformly sampled from 2014–2023 US grants (PatentsView bulk data, CC-BY — attribution to PatentsView), 8K context, bf16 LoRA r=64, one epoch, effective batch 16. Final eval loss 0.8224.

Contamination statement: trained exclusively on pre-2024 grants; evaluate on 2024+ grants only.

Scope and limits: pilot for pipeline validation — keep input descriptions under ~6,000 tokens; dependent-claim completeness is the known weak suit. Larger paper-grade models (Qwen-14B, Gemma-4-31B, 16K context, full 616K-example corpus) are trained separately. Not legal advice; outputs require attorney review.

Prompt format: system prompt "You are an experienced patent attorney drafting US utility patent documents..." then user: "Draft the complete claim set for a patent application based on the following detailed description of the invention." followed by "=== DETAILED DESCRIPTION ===" and the description text.

Citation

@misc{MikeTeodorescu_2026patentllmclaims,
  author       = {Mike Teodorescu},
  title        = {Llama-patentLLMClaimsSmall: A Llama-3.1-8B Pilot Model
                  for US Patent Claim Generation},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/miketeod/Llama-patentLLMClaimsSmall}},
  note         = {Fine-tuned on 45,000 US utility patent grants (2014--2023)
                  derived from PatentsView bulk data; 8K context, LoRA r=64}
}

Please also cite the base model (Grattafiori et al., 2024, The Llama 3 Herd of Models, arXiv:2407.21783) and the data source (PatentsView bulk data, CC-BY 4.0, patentsview.org).

Downloads last month: -

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

8-bit

Model tree for miketeod/Llama-patentLLMClaimsSmall

Base model

meta-llama/Llama-3.1-8B

Finetuned

meta-llama/Llama-3.1-8B-Instruct

Quantized

(895)

this model

Paper for miketeod/Llama-patentLLMClaimsSmall

The Llama 3 Herd of Models

Paper • 2407.21783 • Published Jul 31, 2024 • 119