---
base_model: Trelis/Meta-Llama-3-70B-Instruct-function-calling
datasets:
- Trelis/function_calling_v3
extra_gated_prompt: Purchase access to this repo [HERE](https://buy.stripe.com/00g5l6aO9dmbcV201z)!
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- llama 3
---
## About

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static quants of https://huggingface.co/Trelis/Meta-Llama-3-70B-Instruct-function-calling

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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.
## 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/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q2_K.gguf) | Q2_K | 26.5 |  |
| [GGUF](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.IQ3_S.gguf) | IQ3_S | 31.0 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q3_K_S.gguf) | Q3_K_S | 31.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.IQ3_M.gguf) | IQ3_M | 32.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q3_K_M.gguf) | Q3_K_M | 34.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q4_K_S.gguf) | Q4_K_S | 40.4 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q6_K.gguf.part2of2) | Q6_K | 58.0 | very good quality |
| [PART 1](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Meta-Llama-3-70B-Instruct-function-calling-GGUF/resolve/main/Meta-Llama-3-70B-Instruct-function-calling.Q8_0.gguf.part2of2) | Q8_0 | 75.1 | fast, best quality |

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.

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