metadata
language:
- en
library_name: transformers
pipeline_tag: text-generation
datasets:
- jondurbin/airoboros-2.2
- Open-Orca/OpenOrca
- garage-bAInd/Open-Platypus
- WizardLM/WizardLM_evol_instruct_V2_196k
- TokenBender/python_eval_instruct_51k
tags:
- llama-2
- code
- TensorBlock
- GGUF
license: llama2
base_model: uukuguy/speechless-coding-7b-16k-tora
model-index:
- name: SpeechlessCoder
results:
- task:
type: text-generation
dataset:
name: HumanEval
type: openai_humaneval
metrics:
- type: pass@1
value: 52.439
name: pass@1
verified: false
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
uukuguy/speechless-coding-7b-16k-tora - GGUF
This repo contains GGUF format model files for uukuguy/speechless-coding-7b-16k-tora.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| speechless-coding-7b-16k-tora-Q2_K.gguf | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
| speechless-coding-7b-16k-tora-Q3_K_S.gguf | Q3_K_S | 2.948 GB | very small, high quality loss |
| speechless-coding-7b-16k-tora-Q3_K_M.gguf | Q3_K_M | 3.298 GB | very small, high quality loss |
| speechless-coding-7b-16k-tora-Q3_K_L.gguf | Q3_K_L | 3.597 GB | small, substantial quality loss |
| speechless-coding-7b-16k-tora-Q4_0.gguf | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| speechless-coding-7b-16k-tora-Q4_K_S.gguf | Q4_K_S | 3.857 GB | small, greater quality loss |
| speechless-coding-7b-16k-tora-Q4_K_M.gguf | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
| speechless-coding-7b-16k-tora-Q5_0.gguf | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| speechless-coding-7b-16k-tora-Q5_K_S.gguf | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
| speechless-coding-7b-16k-tora-Q5_K_M.gguf | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
| speechless-coding-7b-16k-tora-Q6_K.gguf | Q6_K | 5.529 GB | very large, extremely low quality loss |
| speechless-coding-7b-16k-tora-Q8_0.gguf | Q8_0 | 7.161 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/speechless-coding-7b-16k-tora-GGUF --include "speechless-coding-7b-16k-tora-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/speechless-coding-7b-16k-tora-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'