Add README

README.md

@@ -1,3 +1,96 @@
----
-license: cc-by-sa-4.0
----
+---
+license: cc-by-sa-4.0
+datasets:
+- PJMixers-Dev/dolphin-deepseek-1k-think-1k-response-filtered-ShareGPT
+- Jofthomas/hermes-function-calling-thinking-V1
+language:
+- en
+base_model:
+- arlineka/CatNyanster-7b
+pipeline_tag: text-generation
+---
+# GGUF Files for Blake-XTM-Arc-T0
+
+These are the GGUF files for [Flexan/Blake-XTM-Arc-T0](https://huggingface.co/Flexan/Blake-XTM-Arc-T0).
+
+| GGUF Link | Quantization | Description |
+| ---- | ----- | ----------- |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q2_K.gguf) | Q2_K | Lowest quality |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.IQ3_XS.gguf) | IQ3_XS | Integer quant |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q3_K_S.gguf) | Q3_K_S |  |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.IQ3_S.gguf) | IQ3_S | Integer quant, preferable over Q3_K_S |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.IQ3_M.gguf) | IQ3_M | Integer quant |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q3_K_M.gguf) | Q3_K_M |  |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q3_K_L.gguf) | Q3_K_L |  |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.IQ4_XS.gguf) | IQ4_XS | Integer quant |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q4_K_S.gguf) | Q4_K_S | Fast with good performance |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q4_K_M.gguf) | Q4_K_M | **Recommended:** Perfect mix of speed and performance |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q5_K_S.gguf) | Q5_K_S |  |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q5_K_M.gguf) | Q5_K_M |  |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q6_K.gguf) | Q6_K | Very good quality |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.Q8_0.gguf) | Q8_0 | Best quality |
+| [Download](https://huggingface.co/Flexan/Blake-XTM-Arc-T0-GGUF/resolve/main/Blake-XTM-Arc-T0.f16.gguf) | f16 | Full precision, don't bother; use a quant |
+
+# Model Card for Blake-XTM Arc
+
+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](https://huggingface.co/Flexan/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](https://huggingface.co/arlineka/CatNyanster-7b) as base model, which was fine-tuned on [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1).
+
+### Chat Format
+
+Blake-XTM Arc T0 uses the ChatML format, e.g.:
+```text
+<|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):
+1. Response:
+   ```text
+   <|im_start|>assistant
+   Hello! How may I assist you today?<|im_end|>
+   ```
+2. Tool call:
+   ```text
+   <|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:
+  ```text
+  You are an advanced AI model.
+  ```
+- Thought process and tool calling:
+  ```text
+  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': []}}}] <\/tools>Use the following pydantic model json schema for each tool call you will make: {'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
+
+  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|>
+```