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merge pr/KingBright/13

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jhqxxx
2026-01-08 00:04:24 +08:00
parent 0cc4880921
commit 618d75b263
15 changed files with 280 additions and 58 deletions
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download_and_run.sh
Executable
+160
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@@ -0,0 +1,160 @@
#!/bin/bash
set -e
# Default values
# MIRROR_URL="https://hf-mirror.com"
DEFAULT_SAVE_DIR="$HOME/.aha"
MODEL_ALIAS=""
# Help function
show_help() {
echo "Usage: $0 [model_alias]"
echo ""
echo "Arguments:"
echo " model_alias The model alias to download (e.g., voxcpm, qwen2.5vl-3b)"
echo ""
echo "Available models:"
echo " minicpm4-0.5b"
echo " qwen2.5vl-3b"
echo " qwen2.5vl-7b"
echo " qwen3vl-2b"
echo " qwen3vl-4b"
echo " qwen3vl-8b"
echo " qwen3vl-32b"
echo " deepseek-ocr"
echo " hunyuan-ocr"
echo " paddleocr-vl"
echo " RMBG2.0"
echo " voxcpm"
echo " voxcpm1.5"
echo " glm-asr-nano-2512"
echo ""
exit 1
}
# Check if model alias is provided
if [ -z "$1" ]; then
show_help
fi
MODEL_ALIAS=$1
# Map alias to Repo ID
MODEL_ID=""
case $MODEL_ALIAS in
"minicpm4-0.5b")
MODEL_ID="OpenBMB/MiniCPM4-0.5B"
;;
"qwen2.5vl-3b")
MODEL_ID="Qwen/Qwen2.5-VL-3B-Instruct"
;;
"qwen2.5vl-7b")
MODEL_ID="Qwen/Qwen2.5-VL-7B-Instruct"
;;
"qwen3vl-2b")
MODEL_ID="Qwen/Qwen3-VL-2B-Instruct"
;;
"qwen3vl-4b")
MODEL_ID="Qwen/Qwen3-VL-4B-Instruct"
;;
"qwen3vl-8b")
MODEL_ID="Qwen/Qwen3-VL-8B-Instruct"
;;
"qwen3vl-32b")
MODEL_ID="Qwen/Qwen3-VL-32B-Instruct"
;;
"deepseek-ocr")
MODEL_ID="deepseek-ai/DeepSeek-OCR"
;;
"hunyuan-ocr")
MODEL_ID="Tencent-Hunyuan/HunyuanOCR"
;;
"paddleocr-vl")
MODEL_ID="PaddlePaddle/PaddleOCR-VL"
;;
"RMBG2.0")
MODEL_ID="AI-ModelScope/RMBG-2.0"
;;
"voxcpm")
MODEL_ID="OpenBMB/VoxCPM-0.5B"
;;
"voxcpm1.5")
MODEL_ID="OpenBMB/VoxCPM1.5"
;;
"glm-asr-nano-2512")
MODEL_ID="zai-org/GLM-ASR-Nano-2512"
;;
*)
echo "Error: Unknown model alias '$MODEL_ALIAS'"
show_help
;;
esac
echo "Selected Model: $MODEL_ALIAS"
echo "Repo ID: $MODEL_ID"
echo "Target Directory: $DEFAULT_SAVE_DIR/$MODEL_ID"
# Prepare environment for acceleration (Default to mirror if not set)
if [ -z "$HF_ENDPOINT" ]; then
export HF_ENDPOINT=$MIRROR_URL
echo "Using default HF Mirror: $HF_ENDPOINT"
else
echo "Using custom HF Endpoint: $HF_ENDPOINT"
fi
# Check if huggingface-cli and hf_transfer are installed
CLI_CMD=""
if command -v huggingface-cli &> /dev/null; then
CLI_CMD="huggingface-cli"
elif command -v hf &> /dev/null; then
CLI_CMD="hf"
else
echo "huggingface-cli not found. Installing via pip..."
if command -v pip3 &> /dev/null; then
pip3 install -U "huggingface_hub[cli]" hf_transfer
elif command -v pip &> /dev/null; then
pip install -U "huggingface_hub[cli]" hf_transfer
else
echo "Error: pip is not available. Please install python and pip."
exit 1
fi
CLI_CMD="huggingface-cli"
fi
# Try to install hf_transfer if simple python check fails (optional but recommended for speed)
if ! python3 -c "import hf_transfer" &> /dev/null; then
echo "Installing hf_transfer for faster downloads..."
pip3 install -U hf_transfer || echo "Warning: hf_transfer install failed, falling back to standard download."
fi
# Enable HF Transfer (Rust-based downloader) - Default to 1 (On) unless explicitly disabled
export HF_HUB_ENABLE_HF_TRANSFER=${HF_HUB_ENABLE_HF_TRANSFER:-1}
if [ "$HF_HUB_ENABLE_HF_TRANSFER" == "1" ]; then
echo "Enabled HF_HUB_ENABLE_HF_TRANSFER for high-speed download"
else
echo "HF_HUB_ENABLE_HF_TRANSFER disabled. Using standard Python downloader."
fi
# Download model
echo "Downloading model with acceleration via $CLI_CMD..."
# Note: --resume-download is deprecated/implicit in newer versions, removing it.
# --local-dir-use-symlinks matches standard CLI if version is recent.
if ! $CLI_CMD download "$MODEL_ID" --local-dir "$DEFAULT_SAVE_DIR/$MODEL_ID" --local-dir-use-symlinks False $TOKEN_ARG; then
echo ""
echo "Error: Download failed."
echo "If you received a 429 Rate Limit error, please provide a Hugging Face Token."
echo "Usage: ./download_and_run.sh $MODEL_ALIAS [hf_token]"
echo "Or set the HF_TOKEN environment variable."
exit 1
fi
# Run cargo
echo "Starting application with cargo..."
# Detect if on Mac to add 'metal' feature
if [[ "$OSTYPE" == "darwin"* ]]; then
echo "Detected MacOS. Running with 'metal' feature..."
cargo run -r --features metal -- --model "$MODEL_ALIAS" --weight-path "$DEFAULT_SAVE_DIR/$MODEL_ID"
else
echo "Running with default features (cuda)..."
cargo run -r --features cuda -- --model "$MODEL_ALIAS" --weight-path "$DEFAULT_SAVE_DIR/$MODEL_ID"
fi
src/models/voxcpm/generate.rs
+4
View File
@@ -199,6 +199,10 @@ impl VoxCPMGenerate {
)?;
Ok(audio)
}
pub fn sample_rate(&self) -> usize {
self.sample_rate
}
}
impl GenerateModel for VoxCPMGenerate {
tests/test_deepseek_ocr.rs
+8 -4
View File
@@ -32,10 +32,12 @@ fn deepseek_ocr_generate() -> Result<()> {
"metadata": {"base_size": "640", "image_size": "640", "crop_mode": "false"}
}
"#;
let model_path = "/home/jhq/huggingface_model/deepseek-ai/DeepSeek-OCR/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/deepseek-ai/DeepSeek-OCR/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = DeepseekOCRGenerateModel::init(model_path, None, None)?;
let mut model = DeepseekOCRGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let i_start = Instant::now();
@@ -84,10 +86,12 @@ async fn deepseek_ocr_stream() -> Result<()> {
"metadata": {"base_size": "640", "image_size": "640", "crop_mode": "false"}
}
"#;
let model_path = "/home/jhq/huggingface_model/deepseek-ai/DeepSeek-OCR/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/deepseek-ai/DeepSeek-OCR/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = DeepseekOCRGenerateModel::init(model_path, None, None)?;
let mut model = DeepseekOCRGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let mut stream = pin!(model.generate_stream(mes)?);
tests/test_gelab_zero.rs
+4 -2
View File
@@ -8,7 +8,9 @@ use anyhow::Result;
fn gelab_zero_generate() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda gelab_zero_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/stepfun-ai/GELab-Zero-4B-preview";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/stepfun-ai/GELab-Zero-4B-preview", save_dir);
let message = r#"
{
@@ -56,7 +58,7 @@ fn gelab_zero_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut qwen3vl = Qwen3VLGenerateModel::init(model_path, None, None)?;
let mut qwen3vl = Qwen3VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_glm_asr_nano.rs
+8 -4
View File
@@ -8,7 +8,9 @@ use rocket::futures::StreamExt;
#[test]
fn glm_asr_nano_generate() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda glm_asr_nano_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/ZhipuAI/GLM-ASR-Nano-2512/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/ZhipuAI/GLM-ASR-Nano-2512/", save_dir);
let message = r#"
{
"model": "glm-asr-nano",
@@ -34,7 +36,7 @@ fn glm_asr_nano_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut glm_asr_model = GlmAsrNanoGenerateModel::init(model_path, None, None)?;
let mut glm_asr_model = GlmAsrNanoGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let i_start = Instant::now();
@@ -54,7 +56,9 @@ fn glm_asr_nano_generate() -> Result<()> {
#[tokio::test]
async fn glm_asr_nano_stream() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda glm_asr_nano_stream -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/ZhipuAI/GLM-ASR-Nano-2512/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/ZhipuAI/GLM-ASR-Nano-2512/", save_dir);
let message = r#"
{
"model": "glm-asr-nano",
@@ -80,7 +84,7 @@ async fn glm_asr_nano_stream() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut glm_asr_model = GlmAsrNanoGenerateModel::init(model_path, None, None)?;
let mut glm_asr_model = GlmAsrNanoGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let i_start = Instant::now();
tests/test_hunyuan_ocr.rs
+8 -4
View File
@@ -31,10 +31,12 @@ fn hunyuan_ocr_generate() -> Result<()> {
]
}
"#;
let model_path = "/home/jhq/huggingface_model/Tencent-Hunyuan/HunyuanOCR/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Tencent-Hunyuan/HunyuanOCR/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = HunyuanOCRGenerateModel::init(model_path, None, None)?;
let mut model = HunyuanOCRGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let i_start = Instant::now();
@@ -79,10 +81,12 @@ async fn hunyuan_ocr_stream() -> Result<()> {
]
}
"#;
let model_path = "/home/jhq/huggingface_model/Tencent-Hunyuan/HunyuanOCR/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Tencent-Hunyuan/HunyuanOCR/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = HunyuanOCRGenerateModel::init(model_path, None, None)?;
let mut model = HunyuanOCRGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let mut stream = pin!(model.generate_stream(mes)?);
tests/test_minicpm4.rs
+8 -4
View File
@@ -11,7 +11,9 @@ fn minicpm_generate() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda minicpm_generate -r -- --nocapture
// test with cuda+flash-attn: RUST_BACKTRACE=1 cargo test -F cuda,flash-attn minicpm_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/OpenBMB/MiniCPM4-0.5B/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/MiniCPM4-0.5B/", save_dir);
let message = r#"
{
"temperature": 0.3,
@@ -27,7 +29,7 @@ fn minicpm_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = MiniCPMGenerateModel::init(model_path, None, None)?;
let mut model = MiniCPMGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -50,7 +52,9 @@ fn minicpm_generate() -> Result<()> {
async fn minicpm_stream() -> Result<()> {
// test with cuda+flash-attn: RUST_BACKTRACE=1 cargo test -F cuda,flash-attn minicpm_stream -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/OpenBMB/MiniCPM4-0.5B/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/MiniCPM4-0.5B/", save_dir);
let message = r#"
{
@@ -65,7 +69,7 @@ async fn minicpm_stream() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = MiniCPMGenerateModel::init(model_path, None, None)?;
let mut model = MiniCPMGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_paddleocr_vl.rs
+8 -4
View File
@@ -32,10 +32,12 @@ fn paddleocr_vl_generate() -> Result<()> {
"stream": false
}
"#;
let model_path = "/home/jhq/huggingface_model/PaddlePaddle/PaddleOCR-VL/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/PaddlePaddle/PaddleOCR-VL/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = PaddleOCRVLGenerateModel::init(model_path, None, None)?;
let mut model = PaddleOCRVLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let i_start = Instant::now();
@@ -79,10 +81,12 @@ async fn paddleocr_vl_stream() -> Result<()> {
]
}
"#;
let model_path = "/home/jhq/huggingface_model/PaddlePaddle/PaddleOCR-VL/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/PaddlePaddle/PaddleOCR-VL/", save_dir);
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = PaddleOCRVLGenerateModel::init(model_path, None, None)?;
let mut model = PaddleOCRVLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let mut stream = pin!(model.generate_stream(mes)?);
tests/test_qwen2_5vl.rs
+8 -4
View File
@@ -13,7 +13,9 @@ fn qwen2_5vl_generate() -> Result<()> {
// let device = Device::cuda_if_available(0)?;
// let dtype = DType::BF16;
let model_path = "/home/jhq/huggingface_model/Qwen/Qwen2.5-VL-3B-Instruct/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Qwen/Qwen2.5-VL-3B-Instruct/", save_dir);
let message = r#"
{
@@ -40,7 +42,7 @@ fn qwen2_5vl_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = Qwen2_5VLGenerateModel::init(model_path, None, None)?;
let mut model = Qwen2_5VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -65,7 +67,9 @@ async fn qwen2_5vl_stream() -> Result<()> {
// let device = Device::cuda_if_available(0)?;
// let dtype = DType::BF16;
let model_path = "/home/jhq/huggingface_model/Qwen/Qwen2.5-VL-3B-Instruct/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Qwen/Qwen2.5-VL-3B-Instruct/", save_dir);
let message = r#"
{
@@ -92,7 +96,7 @@ async fn qwen2_5vl_stream() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = Qwen2_5VLGenerateModel::init(model_path, None, None)?;
let mut model = Qwen2_5VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_qwen3vl.rs
+8 -4
View File
@@ -9,7 +9,9 @@ use rocket::futures::StreamExt;
fn qwen3vl_generate() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda,ffmpeg qwen3vl_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/Qwen/Qwen3-VL-2B-Instruct/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Qwen/Qwen3-VL-2B-Instruct/", save_dir);
let message = r#"
{
@@ -36,7 +38,7 @@ fn qwen3vl_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut qwen3vl = Qwen3VLGenerateModel::init(model_path, None, None)?;
let mut qwen3vl = Qwen3VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -58,7 +60,9 @@ fn qwen3vl_generate() -> Result<()> {
async fn qwen3vl_stream() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda,ffmpeg qwen3vl_stream -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/Qwen/Qwen3-VL-2B-Instruct/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Qwen/Qwen3-VL-2B-Instruct/", save_dir);
let message = r#"
{
@@ -85,7 +89,7 @@ async fn qwen3vl_stream() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut qwen3vl = Qwen3VLGenerateModel::init(model_path, None, None)?;
let mut qwen3vl = Qwen3VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_rmbg2_0.rs
+4 -2
View File
@@ -8,7 +8,9 @@ use anyhow::Result;
fn rmbg2_0_generate() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda rmbg2_0_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/AI-ModelScope/RMBG-2.0/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/AI-ModelScope/RMBG-2.0/", save_dir);
let message = r#"
{
@@ -31,7 +33,7 @@ fn rmbg2_0_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let model = RMBG2_0Model::init(model_path, None, None)?;
let model = RMBG2_0Model::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_robo_brain.rs
+4 -2
View File
@@ -8,7 +8,9 @@ use anyhow::Result;
fn robo_brain_generate() -> Result<()> {
// test with cuda: RUST_BACKTRACE=1 cargo test -F cuda robo_brain_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/BAAI/RoboBrain2.0-3B/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/BAAI/RoboBrain2.0-3B/", save_dir);
let message = r#"
{
@@ -28,7 +30,7 @@ fn robo_brain_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut model = Qwen2_5VLGenerateModel::init(model_path, None, None)?;
let mut model = Qwen2_5VLGenerateModel::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
tests/test_voxcpm.rs
+12 -6
View File
@@ -13,7 +13,9 @@ use anyhow::{Ok, Result};
#[test]
fn voxcpm_use_message_generate() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda voxcpm_use_message_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/openbmb/VoxCPM-0.5B/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
let message = r#"
{
"model": "voxcpm",
@@ -40,7 +42,7 @@ fn voxcpm_use_message_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut voxcpm_generate = VoxCPMGenerate::init(model_path, None, None)?;
let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -59,10 +61,12 @@ fn voxcpm_use_message_generate() -> Result<()> {
#[test]
fn voxcpm_generate() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda voxcpm_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/openbmb/VoxCPM-0.5B/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
let i_start = Instant::now();
let mut voxcpm_generate = VoxCPMGenerate::init(model_path, None, None)?;
let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -106,8 +110,10 @@ fn voxcpm_generate() -> Result<()> {
#[test]
fn voxcpm_tokenizer() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/openbmb/VoxCPM-0.5B/";
let tokenizer = SingleChineseTokenizer::new(model_path)?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
let tokenizer = SingleChineseTokenizer::new(&model_path)?;
let ids = tokenizer.encode("你好啊，你吃饭了吗".to_string())?;
println!("ids: {:?}", ids);
Ok(())
tests/test_voxcpm1_5.rs
+12 -6
View File
@@ -13,7 +13,9 @@ use anyhow::{Ok, Result};
#[test]
fn voxcpm1_5_use_message_generate() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda voxcpm1_5_use_message_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/OpenBMB/VoxCPM1.5/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM1.5/", save_dir);
let message = r#"
{
"model": "voxcpm1.5",
@@ -40,7 +42,7 @@ fn voxcpm1_5_use_message_generate() -> Result<()> {
"#;
let mes: ChatCompletionParameters = serde_json::from_str(message)?;
let i_start = Instant::now();
let mut voxcpm_generate = VoxCPMGenerate::init(model_path, None, None)?;
let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -58,10 +60,12 @@ fn voxcpm1_5_use_message_generate() -> Result<()> {
#[test]
fn voxcpm1_5_generate() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda voxcpm1_5_generate -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/OpenBMB/VoxCPM1.5/";
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM1.5/", save_dir);
let i_start = Instant::now();
let mut voxcpm_generate = VoxCPMGenerate::init(model_path, None, None)?;
let mut voxcpm_generate = VoxCPMGenerate::init(&model_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
@@ -106,8 +110,10 @@ fn voxcpm1_5_generate() -> Result<()> {
#[test]
fn voxcpm1_5_tokenizer() -> Result<()> {
// RUST_BACKTRACE=1 cargo test -F cuda voxcpm1_5_tokenizer -r -- --nocapture
let model_path = "/home/jhq/huggingface_model/OpenBMB/VoxCPM1.5/";
let tokenizer = SingleChineseTokenizer::new(model_path)?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM1.5/", save_dir);
let tokenizer = SingleChineseTokenizer::new(&model_path)?;
let ids = tokenizer.encode("你好啊，你吃饭了吗".to_string())?;
println!("ids: {:?}", ids);
Ok(())
tests/weight_test.rs
+24 -12
View File
@@ -7,8 +7,10 @@ use candle_nn::VarBuilder;
#[test]
fn minicpm4_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/OpenBMB/MiniCPM4-0.5B/";
let model_list = find_type_files(model_path, "safetensors")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/MiniCPM4-0.5B/", save_dir);
let model_list = find_type_files(&model_path, "safetensors")?;
let device = Device::Cpu;
for m in model_list {
let weights = safetensors::load(m, &device)?;
@@ -23,8 +25,10 @@ fn minicpm4_weight() -> Result<()> {
#[test]
fn voxcpm_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/openbmb/VoxCPM-0.5B/";
let model_list = find_type_files(model_path, "pth")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM-0.5B/", save_dir);
let model_list = find_type_files(&model_path, "pth")?;
println!("model_list: {:?}", model_list);
let dev = get_device(None);
let mut dict_to_hashmap = HashMap::new();
@@ -48,8 +52,10 @@ fn voxcpm_weight() -> Result<()> {
#[test]
fn voxcpm1_5_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/OpenBMB/VoxCPM1.5/";
let model_list = find_type_files(model_path, "pth")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/OpenBMB/VoxCPM1.5/", save_dir);
let model_list = find_type_files(&model_path, "pth")?;
println!("model_list: {:?}", model_list);
// let dev = get_device(None);
let mut dict_to_hashmap = HashMap::new();
@@ -68,8 +74,10 @@ fn voxcpm1_5_weight() -> Result<()> {
#[test]
fn qwen3vl_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/Qwen/Qwen3-VL-4B-Instruct/";
let model_list = find_type_files(model_path, "safetensors")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Qwen/Qwen3-VL-4B-Instruct/", save_dir);
let model_list = find_type_files(&model_path, "safetensors")?;
let device = Device::Cpu;
for m in &model_list {
@@ -84,8 +92,10 @@ fn qwen3vl_weight() -> Result<()> {
#[test]
fn deepseekocr_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/deepseek-ai/DeepSeek-OCR/";
let model_list = find_type_files(model_path, "safetensors")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/deepseek-ai/DeepSeek-OCR/", save_dir);
let model_list = find_type_files(&model_path, "safetensors")?;
let device = Device::Cpu;
for m in &model_list {
@@ -103,8 +113,10 @@ fn deepseekocr_weight() -> Result<()> {
#[test]
fn hunyuanocr_weight() -> Result<()> {
let model_path = "/home/jhq/huggingface_model/Tencent-Hunyuan/HunyuanOCR/";
let model_list = find_type_files(model_path, "safetensors")?;
let save_dir =
aha::utils::get_default_save_dir().ok_or(anyhow::anyhow!("Failed to get save dir"))?;
let model_path = format!("{}/Tencent-Hunyuan/HunyuanOCR/", save_dir);
let model_list = find_type_files(&model_path, "safetensors")?;
let device = Device::Cpu;
for m in &model_list {