Instructions to use julioc-p/CNCF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use julioc-p/CNCF with Transformers:

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

pipe = pipeline("text-generation", model="julioc-p/CNCF")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("julioc-p/CNCF")
model = AutoModelForCausalLM.from_pretrained("julioc-p/CNCF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use julioc-p/CNCF 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 julioc-p/CNCF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf julioc-p/CNCF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf julioc-p/CNCF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf julioc-p/CNCF:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf julioc-p/CNCF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf julioc-p/CNCF:Q4_K_M

Use Docker

docker model run hf.co/julioc-p/CNCF:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use julioc-p/CNCF with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/julioc-p/CNCF:Q4_K_M

SGLang

How to use julioc-p/CNCF 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 "julioc-p/CNCF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "julioc-p/CNCF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "julioc-p/CNCF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "julioc-p/CNCF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use julioc-p/CNCF with Ollama:
```
ollama run hf.co/julioc-p/CNCF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use julioc-p/CNCF with Docker Model Runner:
```
docker model run hf.co/julioc-p/CNCF:Q4_K_M
```

Lemonade

How to use julioc-p/CNCF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull julioc-p/CNCF:Q4_K_M

Run and chat with the model

lemonade run user.CNCF-Q4_K_M

List all available models

lemonade list

Atomic Chat

julioc-p commited on Jun 13, 2024

Commit

fa12dfe

verified ·

1 Parent(s): ffd1909

Delete special_tokens_map.json

Browse files

Files changed (1) hide show

special_tokens_map.json +0 -34

special_tokens_map.json DELETED Viewed

@@ -1,34 +0,0 @@
-{
-  "additional_special_tokens": [
-    "<start_of_turn>",
-    "<end_of_turn>"
-  ],
-  "bos_token": {
-    "content": "<bos>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "eos_token": {
-    "content": "<eos>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "pad_token": {
-    "content": "<pad>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "unk_token": {
-    "content": "<unk>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  }
-}