quantfactory/mental-health-finetuned-mistral-7b-instruct-v0.2-gguf overview

{
  "metadata": {},
  "card_data": {
    "library_name": "transformers",
    "license": "apache-2.0",
    "tags": [
      "autotrain",
      "text-generation-inference",
      "text-generation",
      "peft",
      "generated_from_trainer",
      "mistral",
      "transformers",
      "Inference Endpoints",
      "pytorch"
    ],
    "base_model": "mistralai/Mistral-7B-Instruct-v0.2",
    "model-index": [
      {
        "name": "Mental-Health_ML",
        "results": []
      }
    ],
    "datasets": [
      "Amod/mental_health_counseling_conversations"
    ],
    "inference": true,
    "widget": [
      {
        "messages": [
          {
            "role": "user",
            "content": "What is your favorite condiment?"
          }
        ]
      }
    ],
    "frontmatter": {},
    "hero_image_url": "https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ",
    "summary": "This is quantized version of prabureddy/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2 created using llama.cpp # Original Model Card # Model Trained Using AutoTrain This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the mental_health_counseling_conversations dataset. # Usage ``python from transformers import AutoModelForCausalLM, AutoTokenizer model_path = \"prabureddy/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2\" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, device_map=\"auto\", torch_dtype='auto' ).eval() # Prompt content: \"hi\" messages = [ {\"role\": \"user\", \"content\": \"Hey Alex! I have been feeling a bit down lately.I could really use some advice on how to feel better?\"} ] input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') output_ids = model.generate(input_ids.to('cuda')) response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) # Model response: \"Hello! How can I assist you today?\" print(response) ``",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "\n---\n\nlibrary_name: transformers\nlicense: apache-2.0\ntags:\n- autotrain\n- text-generation-inference\n- text-generation\n- peft\n- generated_from_trainer\n- mistral\n- transformers\n- Inference Endpoints\n- pytorch\nbase_model: mistralai/Mistral-7B-Instruct-v0.2\nmodel-index:\n- name: Mental-Health_ML\n  results: []\ndatasets:\n- Amod/mental_health_counseling_conversations\ninference: true\nwidget:\n- messages:\n  - role: user\n    content: What is your favorite condiment?\n\n---\n\n[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)\n\n\n# QuantFactory/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2-GGUF\nThis is quantized version of [prabureddy/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2](https://huggingface.co/prabureddy/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2) created using llama.cpp\n\n# Original Model Card\n\n\n# Model Trained Using AutoTrain\n\nThis model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the [mental_health_counseling_conversations](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations) dataset.  \n\n# Usage\n\n```python\n\nfrom transformers import AutoModelForCausalLM, AutoTokenizer\n\nmodel_path = \"prabureddy/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2\"\n\ntokenizer = AutoTokenizer.from_pretrained(model_path)\nmodel = AutoModelForCausalLM.from_pretrained(\n    model_path,\n    device_map=\"auto\",\n    torch_dtype='auto'\n).eval()\n\n# Prompt content: \"hi\"\nmessages = [\n    {\"role\": \"user\", \"content\": \"Hey Alex! I have been feeling a bit down lately.I could really use some advice on how to feel better?\"}\n]\n\ninput_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')\noutput_ids = model.generate(input_ids.to('cuda'))\nresponse = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)\n\n# Model response: \"Hello! How can I assist you today?\"\nprint(response)\n```\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "autotrain",
    "text-generation-inference",
    "text-generation",
    "peft",
    "generated_from_trainer",
    "mistral",
    "Inference Endpoints",
    "pytorch",
    "dataset:Amod/mental_health_counseling_conversations",
    "base_model:mistralai/Mistral-7B-Instruct-v0.2",
    "base_model:quantized:mistralai/Mistral-7B-Instruct-v0.2",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 7,
  "downloads": 183,
  "gated": false,
  "private": false,
  "last_modified": "2024-11-11T08:02:56.000Z",
  "created_at": "2024-11-11T07:28:49.000Z",
  "pipeline_tag": "text-generation",
  "library_name": "transformers"
}

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  "id": "QuantFactory/Mental-Health-FineTuned-Mistral-7B-Instruct-v0.2-GGUF",
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  "sha": "8e98d4b3f0ffb6d1130e17e8b622b378dfb3701e",
  "createdAt": "2024-11-11T07:28:49.000Z",
  "lastModified": "2024-11-11T08:02:56.000Z",
  "author": "QuantFactory",
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