Text Generation
Transformers
Safetensors
English
qwen2
audio
speech
conversational
custom_code
text-generation-inference
Instructions to use ddwang2000/EchoChat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ddwang2000/EchoChat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ddwang2000/EchoChat", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ddwang2000/EchoChat", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("ddwang2000/EchoChat", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ddwang2000/EchoChat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ddwang2000/EchoChat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ddwang2000/EchoChat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ddwang2000/EchoChat
- SGLang
How to use ddwang2000/EchoChat 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 "ddwang2000/EchoChat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ddwang2000/EchoChat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "ddwang2000/EchoChat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ddwang2000/EchoChat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ddwang2000/EchoChat with Docker Model Runner:
docker model run hf.co/ddwang2000/EchoChat
Download config.json from ddwang2000/EchoChat: direct link, hf CLI and curl.
- Browser
- Download file 1.34 kB
-
https://huggingface.co/ddwang2000/EchoChat/resolve/main/config.json
- Command line
-
hf download hf://ddwang2000/EchoChat/config.json
-
curl -L -o config.json https://huggingface.co/ddwang2000/EchoChat/resolve/main/config.json
1.34 kB
| { | |
| "architectures": [ | |
| "EchoChatForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_echochat.EchoChatConfig", | |
| "AutoModel": "modeling_echochat.EchoChatModel", | |
| "AutoModelForCausalLM": "modeling_echochat.EchoChatForCausalLM" | |
| }, | |
| "bos_token_id": 151643, | |
| "eos_token_ids": [ | |
| 151644, | |
| 151645 | |
| ], | |
| "hidden_act": "silu", | |
| "hidden_size": 3584, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 18944, | |
| "kimia_adaptor_input_dim": 5120, | |
| "kimia_audio_output_vocab": 16896, | |
| "kimia_media_begin": 151661, | |
| "kimia_media_end": 151663, | |
| "kimia_mimo_audiodelaytokens": 6, | |
| "kimia_mimo_layers": 6, | |
| "kimia_mimo_transformer_from_layer_index": 21, | |
| "kimia_text_output_vocab": 152064, | |
| "kimia_token_offset": 152064, | |
| "max_position_embeddings": 8192, | |
| "max_window_layers": 28, | |
| "model_type": "qwen2", | |
| "num_attention_heads": 28, | |
| "num_audio_special_tokens": 512, | |
| "num_base_tokens": 151643, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 152063, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.3", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "use_whisper_feature": true, | |
| "vocab_size": 168448 | |
| } | |