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

Libraries

How to use JazerJu/VideoMiner with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="JazerJu/VideoMiner",
	filename="fun-asr/Fun-ASR-Nano-Decoder.q5_k.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use JazerJu/VideoMiner with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JazerJu/VideoMiner:Q8_0
# Run inference directly in the terminal:
llama cli -hf JazerJu/VideoMiner:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JazerJu/VideoMiner:Q8_0
# Run inference directly in the terminal:
llama cli -hf JazerJu/VideoMiner:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf JazerJu/VideoMiner:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf JazerJu/VideoMiner:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf JazerJu/VideoMiner:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf JazerJu/VideoMiner:Q8_0

Use Docker

docker model run hf.co/JazerJu/VideoMiner:Q8_0

LM Studio
Jan
Ollama
How to use JazerJu/VideoMiner with Ollama:
```
ollama run hf.co/JazerJu/VideoMiner:Q8_0
```

Unsloth Studio

How to use JazerJu/VideoMiner with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for JazerJu/VideoMiner to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for JazerJu/VideoMiner to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for JazerJu/VideoMiner to start chatting

How to use JazerJu/VideoMiner with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JazerJu/VideoMiner:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "JazerJu/VideoMiner:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use JazerJu/VideoMiner with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JazerJu/VideoMiner:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default JazerJu/VideoMiner:Q8_0

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use JazerJu/VideoMiner with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JazerJu/VideoMiner:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "JazerJu/VideoMiner:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use JazerJu/VideoMiner with Docker Model Runner:
```
docker model run hf.co/JazerJu/VideoMiner:Q8_0
```

Lemonade

How to use JazerJu/VideoMiner with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull JazerJu/VideoMiner:Q8_0

Run and chat with the model

lemonade run user.VideoMiner-Q8_0

List all available models

lemonade list

JazerJu commited on 27 days ago

Commit

1eae9f7

verified ·

1 Parent(s): 34d422c

Add BGE-small-zh-v1.5 ONNX embedding model

Browse files

Files changed (6) hide show

embedding/bge-small-zh-v1.5-onnx/config.json +31 -0
embedding/bge-small-zh-v1.5-onnx/model.onnx +3 -0
embedding/bge-small-zh-v1.5-onnx/special_tokens_map.json +37 -0
embedding/bge-small-zh-v1.5-onnx/tokenizer.json +0 -0
embedding/bge-small-zh-v1.5-onnx/tokenizer_config.json +58 -0
embedding/bge-small-zh-v1.5-onnx/vocab.txt +0 -0

embedding/bge-small-zh-v1.5-onnx/config.json ADDED Viewed

	@@ -0,0 +1,31 @@

+{
+  "architectures": [
+    "BertModel"
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+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
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+  "hidden_size": 512,
+  "id2label": {
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+  "intermediate_size": 2048,
+  "label2id": {
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+  "max_position_embeddings": 512,
+  "model_type": "bert",
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+  "num_hidden_layers": 4,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.57.6",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 21128
+}

embedding/bge-small-zh-v1.5-onnx/model.onnx ADDED Viewed

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

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+size 94835369

embedding/bge-small-zh-v1.5-onnx/special_tokens_map.json ADDED Viewed

	@@ -0,0 +1,37 @@

+{
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "normalized": false,
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+  }
+}

embedding/bge-small-zh-v1.5-onnx/tokenizer.json ADDED Viewed

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embedding/bge-small-zh-v1.5-onnx/tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,58 @@

+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

embedding/bge-small-zh-v1.5-onnx/vocab.txt ADDED Viewed

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