base_model: Darkknight535/OpenCrystal-12B-L3
library_name: transformers
tags:
- not-for-all-audiences
- llama-cpp
- gguf-my-repo
model-index:
- name: OpenCrystal-12B-L3
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 40.71
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 31.84
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 7.93
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 7.49
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 5.74
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 29.34
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Darkknight535/OpenCrystal-12B-L3
name: Open LLM Leaderboard
Triangle104/OpenCrystal-12B-L3-Q5_K_S-GGUF
This model was converted to GGUF format from Darkknight535/OpenCrystal-12B-L3 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Model details:
OpenCrystal-12B-L3
This is a finetuned language model. (I recommend using this one v2 and v2.1 are not good enough)
Rohma 128K??
L3.1 Variant here Instruct Template
Default llama3 instruct and context preset, but here is the one i use. Instruct Context Samplers Creative
Temp : 1.23 Min P : 0.05 Repetition Penalty : 1.05
[And everything else neutral]
Normal
Temp : 0.6 - 0.8 Min P : 0.1 Repetition Penalty : 1.1
[And everything else neutral]
Pro Tip
You can uncheck Include Names option in sillytavern, to force it to speak as others dynamically. Not Recommended
Features
Can speak as other npc automatically.
Creative (Swipes are crazy.)
Coherent (Sometime gets horny)
Output feels like you're using Character.ai
Follows prompt better
Likes higher context length. (12K easily tested)
can summarize and generate image prompts well [The Above image's prompt is generated in a roleplay by this model] (Possible : Due to llama-3-instruct as base)
Instruct Prompt
You're {{char}}, follow {{char}} personality and plot of the story, Don't impersonate as {{user}}, Speak as others NPC except {{user}} when needed. Be Creative, Create various interesting events and situations during the story.
FeedBack
FeedBack here Open LLM Leaderboard Evaluation Results
Detailed results can be found here Metric Value Avg. 20.51 IFEval (0-Shot) 40.71 BBH (3-Shot) 31.84 MATH Lvl 5 (4-Shot) 7.93 GPQA (0-shot) 7.49 MuSR (0-shot) 5.74 MMLU-PRO (5-shot) 29.34
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Triangle104/OpenCrystal-12B-L3-Q5_K_S-GGUF --hf-file opencrystal-12b-l3-q5_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/OpenCrystal-12B-L3-Q5_K_S-GGUF --hf-file opencrystal-12b-l3-q5_k_s.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Triangle104/OpenCrystal-12B-L3-Q5_K_S-GGUF --hf-file opencrystal-12b-l3-q5_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/OpenCrystal-12B-L3-Q5_K_S-GGUF --hf-file opencrystal-12b-l3-q5_k_s.gguf -c 2048