auto-patch README.md

README.md

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+---
+base_model: pints-ai/1.5-Pints-16K-v0.1
+datasets:
+- pints-ai/Expository-Prose-V1
+- HuggingFaceH4/ultrachat_200k
+- Open-Orca/SlimOrca-Dedup
+- meta-math/MetaMathQA
+- HuggingFaceH4/deita-10k-v0-sft
+- WizardLM/WizardLM_evol_instruct_V2_196k
+- togethercomputer/llama-instruct
+- LDJnr/Capybara
+- HuggingFaceH4/ultrafeedback_binarized
+extra_gated_fields:
+  Company: text
+  Country: country
+  I agree to use this model for in accordance to the afore-mentioned Terms of Use: checkbox
+  I want to use this model for:
+    options:
+    - Research
+    - Education
+    - label: Other
+      value: other
+    type: select
+  Specific date: date_picker
+extra_gated_prompt: Though best efforts has been made to ensure, as much as possible,
+  that all texts in the training corpora are royalty free, this does not constitute
+  a legal guarantee that such is the case. **By using any of the models, corpora or
+  part thereof, the user agrees to bear full responsibility to do the necessary due
+  diligence to ensure that he / she is in compliance with their local copyright laws.
+  Additionally, the user agrees to bear any damages arising as a direct cause (or
+  otherwise) of using any artifacts released by the pints research team, as well as
+  full responsibility for the consequences of his / her usage (or implementation)
+  of any such released artifacts. The user also indemnifies Pints Research Team (and
+  any of its members or agents) of any damage, related or unrelated, to the release
+  or subsequent usage of any findings, artifacts or code by the team. For the avoidance
+  of doubt, any artifacts released by the Pints Research team are done so in accordance
+  with the 'fair use' clause of Copyright Law, in hopes that this will aid the research
+  community in bringing LLMs to the next frontier.
+language:
+- en
+library_name: transformers
+license: mit
+quantized_by: mradermacher
+---
+## About
+
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### vocab_type:  -->
 <!-- ### tags: nicoboss -->
 weighted/imatrix quants of https://huggingface.co/pints-ai/1.5-Pints-16K-v0.1
+
+<!-- provided-files -->
+static quants are available at https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-GGUF
+## Usage
+
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+
+## Provided Quants
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ1_S.gguf) | i1-IQ1_S | 0.5 | for the desperate |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ1_M.gguf) | i1-IQ1_M | 0.5 | mostly desperate |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ2_S.gguf) | i1-IQ2_S | 0.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ2_M.gguf) | i1-IQ2_M | 0.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.7 | very low quality |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 0.7 | IQ3_XXS probably better |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.7 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.8 | IQ3_XS probably better |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ3_S.gguf) | i1-IQ3_S | 0.8 | beats Q3_K* |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 0.8 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.9 | IQ3_S probably better |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.9 | IQ3_M probably better |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 1.0 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 1.0 | prefer IQ4_XS |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q4_0.gguf) | i1-Q4_0 | 1.0 | fast, low quality |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 1.0 | optimal size/speed/quality |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 1.1 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q4_1.gguf) | i1-Q4_1 | 1.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 1.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/1.5-Pints-16K-v0.1-i1-GGUF/resolve/main/1.5-Pints-16K-v0.1.i1-Q6_K.gguf) | i1-Q6_K | 1.4 | practically like static Q6_K |
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+
+## FAQ / Model Request
+
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+
+## Thanks
+
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
+
+<!-- end -->