Downloads · 30 days
90
5% of all-time downloads
RichardErkhov/Aculi_-_InternLM2-Chat-20B-ToxicRP-gguf
Aculi_-_InternLM2-Chat-20B-ToxicRP-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
90
5% of all-time downloads
All-time downloads
1.7K
Public
Repo size
200 GB
Likes
0
Public
Click a slice to open those files.
.gguf236 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
InternLM2-Chat-20B-ToxicRP - GGUF
| 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 |
base_model:

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
This model was merged using the passthrough merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 48]
model: output/intervitens_internlm2-limarp-chat-20b-2+Fischerboot/InternLM2-ToxicRP-QLORA-4Bit