Instructions to use basically-ai/Pebble-10M-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use basically-ai/Pebble-10M-Chat with Transformers:

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

pipe = pipeline("text-generation", model="basically-ai/Pebble-10M-Chat", trust_remote_code=True)

# Load model directly
from transformers import Pebble10MLM
model = Pebble10MLM.from_pretrained("basically-ai/Pebble-10M-Chat", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use basically-ai/Pebble-10M-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "basically-ai/Pebble-10M-Chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "basically-ai/Pebble-10M-Chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/basically-ai/Pebble-10M-Chat

SGLang

How to use basically-ai/Pebble-10M-Chat 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 "basically-ai/Pebble-10M-Chat" \
    --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": "basically-ai/Pebble-10M-Chat",
		"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 "basically-ai/Pebble-10M-Chat" \
        --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": "basically-ai/Pebble-10M-Chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use basically-ai/Pebble-10M-Chat with Docker Model Runner:
```
docker model run hf.co/basically-ai/Pebble-10M-Chat
```

Pebble-10M-Chat / config.json

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Upload fine-tuned Pebble-10M-Chat model

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	{
	"architectures": [
	"Pebble10MLM"
	],
	"attention": {
	"is_causal": true,
	"rope_theta": 10000.0
	},
	"auto_map": {
	"AutoConfig": "configuration_pebble.PebbleConfig",
	"AutoModelForCausalLM": "modeling_pebble.PebbleForCausalLM"
	},
	"block_pattern": "mmma\|mmma",
	"dtype": "float32",
	"hidden_size": 384,
	"hybrid_ratio": "3:1 mamba2:attention",
	"intermediate_size": 1536,
	"mamba2": {
	"d_conv": 4,
	"d_state": 128,
	"expand": 2,
	"headdim": 96,
	"use_mem_eff_path": true
	},
	"max_position_embeddings": 512,
	"model_type": "pebble_10m",
	"num_attention_heads": 6,
	"num_hidden_layers": 8,
	"rms_norm_eps": 1e-06,
	"transformers_version": "4.57.1",
	"vocab_size": 2048
	}