Instructions to use pthinc/cicikus_classic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pthinc/cicikus_classic with Transformers:

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

pipe = pipeline("text-generation", model="pthinc/cicikus_classic")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pthinc/cicikus_classic")
model = AutoModelForCausalLM.from_pretrained("pthinc/cicikus_classic", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use pthinc/cicikus_classic 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 pthinc/cicikus_classic:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf pthinc/cicikus_classic:Q4_K_M

Install from WinGet (Windows)

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

Use Docker

docker model run hf.co/pthinc/cicikus_classic:Q4_K_M

LM Studio
Jan

vLLM

How to use pthinc/cicikus_classic with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/pthinc/cicikus_classic:Q4_K_M

SGLang

How to use pthinc/cicikus_classic 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 "pthinc/cicikus_classic" \
    --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": "pthinc/cicikus_classic",
		"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 "pthinc/cicikus_classic" \
        --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": "pthinc/cicikus_classic",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use pthinc/cicikus_classic with Ollama:
```
ollama run hf.co/pthinc/cicikus_classic:Q4_K_M
```

Unsloth Studio

How to use pthinc/cicikus_classic 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 pthinc/cicikus_classic 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 pthinc/cicikus_classic to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for pthinc/cicikus_classic to start chatting

Docker Model Runner
How to use pthinc/cicikus_classic with Docker Model Runner:
```
docker model run hf.co/pthinc/cicikus_classic:Q4_K_M
```

Lemonade

How to use pthinc/cicikus_classic with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull pthinc/cicikus_classic:Q4_K_M

Run and chat with the model

lemonade run user.cicikus_classic-Q4_K_M

List all available models

lemonade list

Atomic Chat

prometechinc commited on Mar 18

Commit

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1 Parent(s): 5be6fa8

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Files changed (3) hide show

config.json +43 -0
generation_config.json +6 -0
model.safetensors +3 -0

config.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "activation_function": "gelu_new",
+  "add_cross_attention": false,
+  "architectures": [
+    "GPT2LMHeadModel"
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+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "dtype": "float16",
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
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+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,6 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "5.0.0"
+}

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