magnum-32b-v2_exl2_4.7bpw_rpcal_mk2

magnum-32b-v2 - EXL2 4.7bpw rpcal mk2

This is a 4.7bpw EXL2 quant of anthracite-org/magnum-32b-v2

This quant was made using exllamav2-0.1.8 with Bluemoon-light dataset for RP.

I tested this quant shortly in some random RPs (including ones over 8k context) and it seems to work fine.

Prompt Templates

Uses ChatML format like mentioned below.

Original readme below

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This is the third in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of Qwen1.5 32B.

Prompting

Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:

"""<|im_start|>user
Hi there!<|im_end|>
<|im_start|>assistant
Nice to meet you!<|im_end|>
<|im_start|>user
Can I ask a question?<|im_end|>
<|im_start|>assistant
"""

Credits

• Stheno dataset (filtered)
• NobodyExistsOnTheInternet/claude_3.5s_single_turn_unslop_filtered
• NobodyExistsOnTheInternet/PhiloGlanSharegpt
• NobodyExistsOnTheInternet/Magpie-Reasoning-Medium-Subset
• kalomaze/Opus_Instruct_25k
• Nopm/Opus_WritingStruct
• Gryphe/Sonnet3.5-SlimOrcaDedupCleaned (A ~16k rows subset)

This model has been a team effort, and the credits goes to all members of Anthracite.

Training

The training was done for 2 epochs. We used 8x NVIDIA H100 Tensor Core GPUs for the full-parameter fine-tuning of the model.

<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>

Safety

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