Instructions to use hf-internal-testing/tiny-random-TransfoXLLMHeadModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hf-internal-testing/tiny-random-TransfoXLLMHeadModel with Transformers:

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

pipe = pipeline("text-generation", model="hf-internal-testing/tiny-random-TransfoXLLMHeadModel")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-random-TransfoXLLMHeadModel", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use hf-internal-testing/tiny-random-TransfoXLLMHeadModel with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/hf-internal-testing/tiny-random-TransfoXLLMHeadModel

SGLang

How to use hf-internal-testing/tiny-random-TransfoXLLMHeadModel 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 "hf-internal-testing/tiny-random-TransfoXLLMHeadModel" \
    --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": "hf-internal-testing/tiny-random-TransfoXLLMHeadModel",
		"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 "hf-internal-testing/tiny-random-TransfoXLLMHeadModel" \
        --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": "hf-internal-testing/tiny-random-TransfoXLLMHeadModel",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use hf-internal-testing/tiny-random-TransfoXLLMHeadModel with Docker Model Runner:
```
docker model run hf.co/hf-internal-testing/tiny-random-TransfoXLLMHeadModel
```

tiny-random-TransfoXLLMHeadModel

File size: 848 Bytes

e0d4ceb

{
  "_name_or_path": "temp/dummy/transfo-xl/TransfoXLLMHeadModel",
  "adaptive": true,
  "architectures": [
    "TransfoXLLMHeadModel"
  ],
  "attn_type": 0,
  "clamp_len": 15,
  "cutoffs": [
    10,
    50,
    80
  ],
  "d_embed": 32,
  "d_head": 8,
  "d_inner": 128,
  "d_model": 32,
  "div_val": 2,
  "dropatt": 0.0,
  "dropout": 0.1,
  "eos_token_id": 0,
  "init": "normal",
  "init_range": 0.01,
  "init_std": 0.02,
  "is_decoder": true,
  "layer_norm_epsilon": 1e-05,
  "mem_len": 30,
  "model_type": "transfo-xl",
  "n_head": 4,
  "n_layer": 5,
  "pad_token_id": 267734,
  "pre_lnorm": false,
  "proj_init_std": 0.01,
  "same_length": true,
  "sample_softmax": -1,
  "tie_projs": [
    false,
    true,
    true,
    true
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.25.0.dev0",
  "untie_r": true,
  "vocab_size": 267735
}