Instructions to use palette-lab/songgot-l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use palette-lab/songgot-l with Transformers:

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

pipe = pipeline("text-generation", model="palette-lab/songgot-l")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("palette-lab/songgot-l")
model = AutoModelForCausalLM.from_pretrained("palette-lab/songgot-l", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use palette-lab/songgot-l 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 palette-lab/songgot-l:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf palette-lab/songgot-l:Q4_K_M

Install from WinGet (Windows)

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

Use Docker

docker model run hf.co/palette-lab/songgot-l:Q4_K_M

LM Studio
Jan

vLLM

How to use palette-lab/songgot-l with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/palette-lab/songgot-l:Q4_K_M

SGLang

How to use palette-lab/songgot-l 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 "palette-lab/songgot-l" \
    --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": "palette-lab/songgot-l",
		"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 "palette-lab/songgot-l" \
        --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": "palette-lab/songgot-l",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use palette-lab/songgot-l with Ollama:
```
ollama run hf.co/palette-lab/songgot-l:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use palette-lab/songgot-l with Docker Model Runner:
```
docker model run hf.co/palette-lab/songgot-l:Q4_K_M
```

Lemonade

How to use palette-lab/songgot-l with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull palette-lab/songgot-l:Q4_K_M

Run and chat with the model

lemonade run user.songgot-l-Q4_K_M

List all available models

lemonade list

Atomic Chat

Hanish commited on 5 days ago

Commit

4c5068b

verified ·

1 Parent(s): 360b7b9

Songgot-nano weights, 24B tokens, 3 epochs, v8 set

Browse files

Files changed (4) hide show

config.json +29 -0
model.safetensors +3 -0
tokenizer.model +3 -0
tokenizer_config.json +16 -0

config.json ADDED Viewed

	@@ -0,0 +1,29 @@

+{
+  "architectures": [
+    "LlamaForCausalLM"
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+  "attention_bias": false,
+  "attention_dropout": 0.0,
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+  "eos_token_id": 2,
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+  "hidden_act": "silu",
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+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.3",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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tokenizer.model ADDED Viewed

	@@ -0,0 +1,3 @@

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tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,16 @@

+{
+ "bos_token": "<s>",
+ "eos_token": "</s>",
+ "pad_token": "<|pad|>",
+ "unk_token": "<unk>",
+ "additional_special_tokens": [
+  "<|system|>",
+  "<|user|>",
+  "<|call|>",
+  "<|end|>",
+  "<|pad|>"
+ ],
+ "model_max_length": 2048,
+ "tokenizer_class": "LlamaTokenizer",
+ "legacy": false
+}