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RichardErkhov/
Aculi_-_InternLM2-Chat-20B-ToxicRP-gguf

Name: Aculi_-_InternLM2-Chat-20B-ToxicRP-gguf
Availability: InStock

endpoints_compatible

gguf

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Quantization made by Richard Erkhov.

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InternLM2-Chat-20B-ToxicRP - GGUF

Model creator: https://huggingface.co/Aculi/
Original model: https://huggingface.co/Aculi/InternLM2-Chat-20B-ToxicRP/

Name	Quant method	Size
InternLM2-Chat-20B-ToxicRP.Q2_K.gguf	Q2_K	7.03GB
InternLM2-Chat-20B-ToxicRP.Q3_K_S.gguf	Q3_K_S	8.16GB
InternLM2-Chat-20B-ToxicRP.Q3_K.gguf	Q3_K	9.05GB
InternLM2-Chat-20B-ToxicRP.Q3_K_M.gguf	Q3_K_M	9.05GB
InternLM2-Chat-20B-ToxicRP.Q3_K_L.gguf	Q3_K_L	9.83GB
InternLM2-Chat-20B-ToxicRP.IQ4_XS.gguf	IQ4_XS	10.12GB
InternLM2-Chat-20B-ToxicRP.Q4_0.gguf	Q4_0	10.55GB
InternLM2-Chat-20B-ToxicRP.IQ4_NL.gguf	IQ4_NL	10.65GB
InternLM2-Chat-20B-ToxicRP.Q4_K_S.gguf	Q4_K_S	10.62GB
InternLM2-Chat-20B-ToxicRP.Q4_K.gguf	Q4_K	11.16GB
InternLM2-Chat-20B-ToxicRP.Q4_K_M.gguf	Q4_K_M	11.16GB
InternLM2-Chat-20B-ToxicRP.Q4_1.gguf	Q4_1	11.67GB
InternLM2-Chat-20B-ToxicRP.Q5_0.gguf	Q5_0	12.79GB
InternLM2-Chat-20B-ToxicRP.Q5_K_S.gguf	Q5_K_S	12.79GB
InternLM2-Chat-20B-ToxicRP.Q5_K.gguf	Q5_K	13.11GB
InternLM2-Chat-20B-ToxicRP.Q5_K_M.gguf	Q5_K_M	13.11GB
InternLM2-Chat-20B-ToxicRP.Q5_1.gguf	Q5_1	13.91GB
InternLM2-Chat-20B-ToxicRP.Q6_K.gguf	Q6_K	15.18GB
InternLM2-Chat-20B-ToxicRP.Q8_0.gguf	Q8_0	19.66GB

Original model description:

base_model:

Fischerboot/InternLM2-ToxicRP-QLORA-4Bit library_name: transformers tags:
mergekit
merge

InternLM2-chat-20B-ToxicRP-QLORA-Merged

This Model was Finetuned by me, using the Machine Power of g4rg. Big Thanks to all people that helped me. Do whatever you want with this Model, just dont do anything illegal.

GGUF here: Aculi/InternLM2-Chat-20B-ToxicRP-GGUF

Have fun

This Model uses CHATML btw.

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

output/intervitens_internlm2-limarp-chat-20b-2 + Fischerboot/InternLM2-ToxicRP-QLORA-4Bit

Configuration

The following YAML configuration was used to produce this model:

yaml

dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 48]
    model: output/intervitens_internlm2-limarp-chat-20b-2+Fischerboot/InternLM2-ToxicRP-QLORA-4Bit

RichardErkhov/Aculi_-_InternLM2-Chat-20B-ToxicRP-gguf