GGUF Files for Blake-XTM-Arc-T0
These are the GGUF files for Flexan/Blake-XTM-Arc-T0.
GGUF Link | Quantization | Description |
---|---|---|
Download | Q2_K | Lowest quality |
Download | IQ3_XS | Integer quant |
Download | Q3_K_S | |
Download | IQ3_S | Integer quant, preferable over Q3_K_S |
Download | IQ3_M | Integer quant |
Download | Q3_K_M | |
Download | Q3_K_L | |
Download | IQ4_XS | Integer quant |
Download | Q4_K_S | Fast with good performance |
Download | Q4_K_M | Recommended: Perfect mix of speed and performance |
Download | Q5_K_S | |
Download | Q5_K_M | |
Download | Q6_K | Very good quality |
Download | Q8_0 | Best quality |
Download | f16 | Full precision, don't bother; use a quant |
Model Card for Blake-XTM Arc T0
Blake-XTM Arc T0 is a 7B large language model used for text generation. It was trained as a (tool-calling) assistant. This model is a variation of Blake-XTM-Arc without reasoning.
Model Details
Model Description
Blake-XTM Arc T0 is a 7B parameter instruct LLM trained to assist and optionally call a tool. It only supports using one tool per assistant message (no parallel tool calling). The model was LoRA fine-tuned with CatNyanster-7B as base model, which was fine-tuned on Mistral-7B.
Chat Format
Blake-XTM Arc T0 uses the ChatML format, e.g.:
<|im_start|>system
System message<|im_end|>
<|im_start|>user
User prompt<|im_end|>
<|im_start|>assistant
Assistant response<|im_end|>
Model Usage
The assistant response can have the following two formats (the contents are examples and were not generated from the model):
- Response:
<|im_start|>assistant Hello! How may I assist you today?<|im_end|>
- Tool call:
<|im_start|>assistant <|tool_start|>{'name': 'find_restaurants', 'arguments': {'city': 'Paris', 'country': 'France'}}<|tool_end|><|im_end|>
We recommend using the following system prompts for your situation:
- Only thought process:
You are an advanced AI model.
- Thought process and tool calling:
You are an advanced AI model with tool-calling capabilities. If the user asks something and it requires a tool then you should call the tool with the arguments. # Tools You have access to the following tools: [{'type': 'function', 'function': {'name': 'convert_currency', 'description': 'Convert currency from one type to another', 'parameters': {'type': 'object', 'properties': {'amount': {'type': 'number', 'description': 'The amount to be converted'}, 'from_currency': {'type': 'string', 'description': 'The currency to convert from'}, 'to_currency': {'type': 'string', 'description': 'The currency to convert to'}}, 'required': ['amount', 'from_currency', 'to_currency']}}}, {'type': 'function', 'function': {'name': 'get_random_joke', 'description': 'Get a random joke', 'parameters': {'type': 'object', 'properties': {}, 'required': []}}}] To call a tool, write a JSON object with the name and arguments inside <|tool_start|>...<|tool_end|>.
For responding with a tool response, you can send a message as the tool
user:
<|im_start|>assistant
<|tool_start|>{'name': 'find_restaurants', 'arguments': {'city': 'Paris', 'country': 'France'}}<|tool_end|><|im_end|>
<|im_start|>tool
{'restaurants': [{'name': 'A Restaurant Name', 'rating': 4.5}]}<|im_end|>
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