Instructions to use kyutai/Sequential_Helium_6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kyutai/Sequential_Helium_6B with Transformers:

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

pipe = pipeline("text-generation", model="kyutai/Sequential_Helium_6B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kyutai/Sequential_Helium_6B")
model = AutoModelForCausalLM.from_pretrained("kyutai/Sequential_Helium_6B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use kyutai/Sequential_Helium_6B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kyutai/Sequential_Helium_6B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kyutai/Sequential_Helium_6B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kyutai/Sequential_Helium_6B

SGLang

How to use kyutai/Sequential_Helium_6B 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 "kyutai/Sequential_Helium_6B" \
    --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": "kyutai/Sequential_Helium_6B",
		"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 "kyutai/Sequential_Helium_6B" \
        --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": "kyutai/Sequential_Helium_6B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use kyutai/Sequential_Helium_6B with Docker Model Runner:
```
docker model run hf.co/kyutai/Sequential_Helium_6B
```

rfbr commited on 6 days ago

Commit

e4d8791

verified ·

1 Parent(s): cefb0c2

Add shuffle_eq_2020 checkpoint

Browse files

Files changed (2) hide show

shuffle_eq_2020/config.json +28 -0
shuffle_eq_2020/model.safetensors +3 -0

shuffle_eq_2020/config.json ADDED Viewed

	@@ -0,0 +1,28 @@

+{
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "architectures": [
+	"LlamaForCausalLM"
+    ],
+    "bos_token_id": 0,
+    "eos_token_id": 1,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "intermediate_size": 11264,
+    "max_position_embeddings": 4096,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 8,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-08,
+    "rope_theta": 100000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.45.0.dev0",
+    "use_cache": true,
+    "vocab_size": 64000
+}

shuffle_eq_2020/model.safetensors ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:30992a1a0fa67a5d56a35342ad246f52ab74a7dbb0b587792cf3038d93bd74bb
+size 12591867056