Model Intelligence Sheet
mradermacher/llama2-7b-medical-finetune_v2-gguf overview
About static quants of https://huggingface.co/TachyHealthResearch/Llama2-7B-Medical-Finetune_V2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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0
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
13 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Llama2-7B-Medical-Finetune_V2.IQ4_XS.gguf | GGUF | IQ4_XS | 3.40 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q2_K.gguf | GGUF | Q2_K | 2.36 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q3_K_L.gguf | GGUF | Q3_K_L | 3.35 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q3_K_M.gguf | GGUF | Q3_K_M | 3.07 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q3_K_S.gguf | GGUF | Q3_K_S | 2.75 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q4_0_4_4.gguf | GGUF | — | 3.56 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q4_K_M.gguf | GGUF | Q4_K_M | 3.80 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q4_K_S.gguf | GGUF | Q4_K_S | 3.59 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q5_K_M.gguf | GGUF | Q5_K_M | 4.45 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q5_K_S.gguf | GGUF | Q5_K_S | 4.33 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q6_K.gguf | GGUF | Q6_K | 5.15 GB | Download |
| Llama2-7B-Medical-Finetune_V2.Q8_0.gguf | GGUF | — | 6.67 GB | Download |
| Llama2-7B-Medical-Finetune_V2.f16.gguf | GGUF | F16 | 12.55 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "TachyHealthResearch/Llama2-7B-Medical-Finetune_V2",
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"trl",
"sft",
"generated_from_trainer"
],
"frontmatter": {
"base_model": "TachyHealthResearch/Llama2-7B-Medical-Finetune_V2",
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"tags": [
"trl",
"sft",
"generated_from_trainer"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/TachyHealthResearch/Llama2-7B-Medical-Finetune_V2 weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: TachyHealthResearch/Llama2-7B-Medical-Finetune_V2\nlanguage:\n- en\nlibrary_name: transformers\nquantized_by: mradermacher\ntags:\n- trl\n- sft\n- generated_from_trainer\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type: -->\n<!-- ### tags: -->\nstatic quants of https://huggingface.co/TachyHealthResearch/Llama2-7B-Medical-Finetune_V2\n\n<!-- provided-files -->\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q2_K.gguf) | Q2_K | 2.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q3_K_S.gguf) | Q3_K_S | 3.0 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q3_K_M.gguf) | Q3_K_M | 3.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q3_K_L.gguf) | Q3_K_L | 3.7 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.IQ4_XS.gguf) | IQ4_XS | 3.7 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q4_0_4_4.gguf) | Q4_0_4_4 | 3.9 | fast on arm, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q4_K_S.gguf) | Q4_K_S | 4.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q4_K_M.gguf) | Q4_K_M | 4.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q5_K_S.gguf) | Q5_K_S | 4.8 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q5_K_M.gguf) | Q5_K_M | 4.9 | |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q6_K.gguf) | Q6_K | 5.6 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.Q8_0.gguf) | Q8_0 | 7.3 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF/resolve/main/Llama2-7B-Medical-Finetune_V2.f16.gguf) | f16 | 13.6 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"trl",
"sft",
"generated_from_trainer",
"en",
"base_model:TachyHealthResearch/Llama2-7B-Medical-Finetune_V2",
"base_model:quantized:TachyHealthResearch/Llama2-7B-Medical-Finetune_V2",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 0,
"downloads": 149,
"gated": false,
"private": false,
"last_modified": "2024-11-04T04:09:21.000Z",
"created_at": "2024-11-04T03:54:01.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "67284559b7d88dbcf9564f24",
"id": "mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF",
"modelId": "mradermacher/Llama2-7B-Medical-Finetune_V2-GGUF",
"sha": "6dee163f14f3231adad44b9cea97df54504a9d9e",
"createdAt": "2024-11-04T03:54:01.000Z",
"lastModified": "2024-11-04T04:09:21.000Z",
"author": "mradermacher",
"downloads": 149,
"likes": 0,
"gated": false,
"private": false,
"pipeline_tag": "",
"library_name": "transformers",
"siblings_count": 15
}