---
base_model: lxcorp/lambda-1v-1B
library_name: transformers
license: mit
language:
- en
- pt
metrics:
- accuracy
pipeline_tag: text-generation
tags:
- hf-inference
- education
- logic
- math
- low-resource
- transformers
- open-source
- causal-lm
- lxcorp
- TensorBlock
- GGUF
---
[](https://tensorblock.co)
[](https://twitter.com/tensorblock_aoi)
[](https://discord.gg/Ej5NmeHFf2)
[](https://github.com/TensorBlock)
[](https://t.me/TensorBlock)
## lxcorp/lambda-1v-1B - GGUF
This repo contains GGUF format model files for [lxcorp/lambda-1v-1B](https://huggingface.co/lxcorp/lambda-1v-1B).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).
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## Prompt template
```
<|system|>
{system_prompt}
<|user|>
{prompt}
<|assistant|>
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [lambda-1v-1B-Q2_K.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q2_K.gguf) | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes |
| [lambda-1v-1B-Q3_K_S.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q3_K_S.gguf) | Q3_K_S | 0.499 GB | very small, high quality loss |
| [lambda-1v-1B-Q3_K_M.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q3_K_M.gguf) | Q3_K_M | 0.548 GB | very small, high quality loss |
| [lambda-1v-1B-Q3_K_L.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q3_K_L.gguf) | Q3_K_L | 0.592 GB | small, substantial quality loss |
| [lambda-1v-1B-Q4_0.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q4_0.gguf) | Q4_0 | 0.637 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [lambda-1v-1B-Q4_K_S.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q4_K_S.gguf) | Q4_K_S | 0.640 GB | small, greater quality loss |
| [lambda-1v-1B-Q4_K_M.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q4_K_M.gguf) | Q4_K_M | 0.668 GB | medium, balanced quality - recommended |
| [lambda-1v-1B-Q5_0.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q5_0.gguf) | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [lambda-1v-1B-Q5_K_S.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q5_K_S.gguf) | Q5_K_S | 0.766 GB | large, low quality loss - recommended |
| [lambda-1v-1B-Q5_K_M.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q5_K_M.gguf) | Q5_K_M | 0.782 GB | large, very low quality loss - recommended |
| [lambda-1v-1B-Q6_K.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q6_K.gguf) | Q6_K | 0.903 GB | very large, extremely low quality loss |
| [lambda-1v-1B-Q8_0.gguf](https://huggingface.co/tensorblock/lxcorp_lambda-1v-1B-GGUF/blob/main/lambda-1v-1B-Q8_0.gguf) | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/lxcorp_lambda-1v-1B-GGUF --include "lambda-1v-1B-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:
```shell
huggingface-cli download tensorblock/lxcorp_lambda-1v-1B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```