Instructions to use voidful/llm-codec-librispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use voidful/llm-codec-librispeech with PEFT:
```
Task type is invalid.
```

How to use voidful/llm-codec-librispeech with Transformers:

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

pipe = pipeline("text-generation", model="voidful/llm-codec-librispeech")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("voidful/llm-codec-librispeech", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use voidful/llm-codec-librispeech with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/voidful/llm-codec-librispeech

SGLang

How to use voidful/llm-codec-librispeech 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 "voidful/llm-codec-librispeech" \
    --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": "voidful/llm-codec-librispeech",
		"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 "voidful/llm-codec-librispeech" \
        --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": "voidful/llm-codec-librispeech",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use voidful/llm-codec-librispeech with Docker Model Runner:
```
docker model run hf.co/voidful/llm-codec-librispeech
```

voidful commited on Jan 3

Commit

b8af831

verified ·

1 Parent(s): 9c3e8fc

Training completed: lora mode

Browse files

Files changed (1) hide show

tokenizer_config.json +4 -0

tokenizer_config.json CHANGED Viewed

@@ -164071,9 +164071,13 @@
   "eos_token": "<|im_end|>",
   "errors": "replace",
   "extra_special_tokens": {},
   "model_max_length": 1010000,
   "pad_token": "<|endoftext|>",
   "split_special_tokens": false,
   "tokenizer_class": "Qwen2Tokenizer",
   "unk_token": null
 }

   "eos_token": "<|im_end|>",
   "errors": "replace",
   "extra_special_tokens": {},
+  "max_length": 4096,
   "model_max_length": 1010000,
   "pad_token": "<|endoftext|>",
   "split_special_tokens": false,
+  "stride": 0,
   "tokenizer_class": "Qwen2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
   "unk_token": null
 }