Update config.json

config.json

@@ -1,19 +1,18 @@
 {
- "model_name": "slim-sentiment-tool",
- "model_ft_base": "slim-sentiment",
+ "model_name": "bling-qa-tool",
+ "model_ft_base": "bling-tiny-llama-1b-v0",
  "quantization": "4Q_K_M GGUF",
  "model_base": "tiny-llama",
- "tokenizer": "llmware/slim-sentiment",
+ "tokenizer": "llmware/bling-tiny-llama-1b-v0",
  "model_type": "llama",
  "parameters": "1.1 billion",
- "description": "slim-sentiment is a function-calling model, fine-tuned to output structured python dictionaries",
+ "description": "bling-qa-tool is a small fast Q&A model intended for use in multi-model local agent deployments",
  "prompt_wrapper": "human_bot",
- "prompt_format": "<human> {context_passage} <classify> sentiment </classify>\n<bot>:",
- "prompt_sample": "<human> That was the best movie I have ever seen. <classify> sentiment </classify>\n<bot>:",
- "output_format": "{'sentiment': ['positive']}",
- "primary_keys": ["sentiment"],
- "output_values": ["positive", "negative", "neutral"],
- "logit_token_markers": [1066, 22198, 17821],
+ "prompt_format": "<human> {context_passage} \n {quick_question} <bot>:",
+ "prompt_sample": "<human> The stock increased by $3 yesterday. \n What was the stock increase yesterday? \n<bot>:",
+ "output_format": "text",
+ "primary_keys": ["quick_question"],
+ "output_values": [],
  "publisher": "llmware",
  "release_date": "february 2024",
  "test_set": [