YAML Metadata
Warning:
The pipeline tag "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, any-to-any, other
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
Locutusque/gpt2-conversational-or-qa - GGUF
This repo contains GGUF format model files for Locutusque/gpt2-conversational-or-qa.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| gpt2-conversational-or-qa-Q2_K.gguf | Q2_K | 0.076 GB | smallest, significant quality loss - not recommended for most purposes |
| gpt2-conversational-or-qa-Q3_K_S.gguf | Q3_K_S | 0.084 GB | very small, high quality loss |
| gpt2-conversational-or-qa-Q3_K_M.gguf | Q3_K_M | 0.091 GB | very small, high quality loss |
| gpt2-conversational-or-qa-Q3_K_L.gguf | Q3_K_L | 0.095 GB | small, substantial quality loss |
| gpt2-conversational-or-qa-Q4_0.gguf | Q4_0 | 0.099 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| gpt2-conversational-or-qa-Q4_K_S.gguf | Q4_K_S | 0.100 GB | small, greater quality loss |
| gpt2-conversational-or-qa-Q4_K_M.gguf | Q4_K_M | 0.105 GB | medium, balanced quality - recommended |
| gpt2-conversational-or-qa-Q5_0.gguf | Q5_0 | 0.114 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| gpt2-conversational-or-qa-Q5_K_S.gguf | Q5_K_S | 0.114 GB | large, low quality loss - recommended |
| gpt2-conversational-or-qa-Q5_K_M.gguf | Q5_K_M | 0.118 GB | large, very low quality loss - recommended |
| gpt2-conversational-or-qa-Q6_K.gguf | Q6_K | 0.129 GB | very large, extremely low quality loss |
| gpt2-conversational-or-qa-Q8_0.gguf | Q8_0 | 0.165 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/gpt2-conversational-or-qa-GGUF --include "gpt2-conversational-or-qa-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/gpt2-conversational-or-qa-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 0
Model tree for tensorblock/gpt2-conversational-or-qa-GGUF
Base model
Locutusque/gpt2-conversational-or-qa