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Model: afrideva/smol_llama-220M-open_instruct-GGUF Source: Original Platform
2026-04-28 23:10:31 +08:00
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+---
+base_model: BEE-spoke-data/smol_llama-220M-open_instruct
+datasets:
+- VMware/open-instruct
+inference: false
+license: apache-2.0
+model_creator: BEE-spoke-data
+model_name: smol_llama-220M-open_instruct
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+widget:
+- example_title: burritos
+  text: "Below is an instruction that describes a task, paired with an input that
+    provides further context. Write a response that appropriately completes the request.
+    \ \n   \n### Instruction:  \n  \nWrite an ode to Chipotle burritos. \n  \n###
+    Response:  \n"
+---
+# BEE-spoke-data/smol_llama-220M-open_instruct-GGUF
+
+Quantized GGUF model files for [smol_llama-220M-open_instruct](https://huggingface.co/BEE-spoke-data/smol_llama-220M-open_instruct) from [BEE-spoke-data](https://huggingface.co/BEE-spoke-data)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [smol_llama-220m-open_instruct.fp16.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.fp16.gguf) | fp16 | 436.50 MB  |
+| [smol_llama-220m-open_instruct.q2_k.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q2_k.gguf) | q2_k | 94.43 MB  |
+| [smol_llama-220m-open_instruct.q3_k_m.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q3_k_m.gguf) | q3_k_m | 114.65 MB  |
+| [smol_llama-220m-open_instruct.q4_k_m.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q4_k_m.gguf) | q4_k_m | 137.58 MB  |
+| [smol_llama-220m-open_instruct.q5_k_m.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q5_k_m.gguf) | q5_k_m | 157.91 MB  |
+| [smol_llama-220m-open_instruct.q6_k.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q6_k.gguf) | q6_k | 179.52 MB  |
+| [smol_llama-220m-open_instruct.q8_0.gguf](https://huggingface.co/afrideva/smol_llama-220M-open_instruct-GGUF/resolve/main/smol_llama-220m-open_instruct.q8_0.gguf) | q8_0 | 232.28 MB  |
+
+
+
+## Original Model Card:
+# BEE-spoke-data/smol_llama-220M-open_instruct
+
+> Please note that this is an experiment, and the model has limitations because it is smol.
+
+
+prompt format is alpaca.
+
+
+```
+Below is an instruction that describes a task, paired with an input that
+provides further context. Write a response that appropriately completes
+the request.  
+
+### Instruction:  
+
+How can I increase my meme production/output? Currently, I only create them in ancient babylonian which is time consuming.  
+
+### Response:
+```
+
+This was **not** trained using a separate 'inputs' field (as `VMware/open-instruct` doesn't use one).
+
+
+## Example
+
+Output on the text above ^. The inference API is set to sample with low temp so you should see (_at least slightly_) different generations each time.
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/MdOB7TD5UosPGZvdZWG0I.png)
+
+Note that the inference API parameters used here are an initial educated guess, and may be updated over time:
+
+```yml
+inference:
+  parameters:
+    do_sample: true
+    renormalize_logits: true
+    temperature: 0.25
+    top_p: 0.95
+    top_k: 50
+    min_new_tokens: 2
+    max_new_tokens: 96
+    repetition_penalty: 1.04
+    no_repeat_ngram_size: 6
+    epsilon_cutoff: 0.0006
+```
+
+Feel free to experiment with the parameters using the model in Python and let us know if you have improved results with other params!
+
+## Data 
+
+This was trained on `VMware/open-instruct` so do whatever you want, provided it falls under the base apache-2.0 license :)
+
+---
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