Base model:finetune:stabilitya... Base model:stabilityai/stablel... Causal lm Conversational Custom code Dataset:teknium/openhermes Dataset:unalignment/toxic-dpo-... Feature-extraction Pytorch Region:us Safetensors Stablelm epoch
Zephyr Quiklang 3B Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
Zephyr Quiklang 3B Parameters and Internals
| LLM Name | Zephyr Quiklang 3B |
| Repository 🤗 | https://huggingface.co/Walmart-the-bag/zephyr-quiklang-3b |
| Base Model(s) | |
| Model Size | 3b |
| Required VRAM | 5.9 GB |
| Updated | 2024-09-19 |
| Maintainer | Walmart-the-bag |
| Model Type | stablelm_epoch |
| Model Files | |
| Model Architecture | StableLMEpochForCausalLM |
| License | other |
| Context Length | 4096 |
| Model Max Length | 4096 |
| Transformers Version | 4.34.1 |
| Tokenizer Class | GPTNeoXTokenizer |
| Padding Token | <|endoftext|> |
| Vocabulary Size | 50304 |
| Torch Data Type | float16 |
Quantized Models of the Zephyr Quiklang 3B
Model |
Likes |
Downloads |
VRAM |
|---|---|---|---|
| Zephyr Quiklang 3B GGUF | 4 | 64 | 1 GB |
| Zephyr Quiklang 3B GPTQ | 1 | 9 | 1 GB |
Best Alternatives to Zephyr Quiklang 3B
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Stable Code 3B Mlx | 16K / 5.6 GB | 5 | 1 |
| Aura 3B | 4K / 5.6 GB | 3 | 2 |
| Slim Extract | 4K / 5.6 GB | 53 | 11 |
| Slim Boolean | 4K / 5.6 GB | 7 | 4 |
| Slim Sa Ner | 4K / 5.6 GB | 10 | 6 |
| Slim Tags 3B | 4K / 5.6 GB | 5 | 4 |
| Slim Summary | 4K / 5.6 GB | 23 | 7 |
| Slim Xsum | 4K / 5.6 GB | 12 | 6 |
| Memphis CoT 3B | 4K / 5.6 GB | 7 | 29 |
| Tofu 3B | 4K / 5.6 GB | 6 | 2 |
Note: green Score (e.g. "73.2") means that the model is better than Walmart-the-bag/zephyr-quiklang-3b .
Rank the Zephyr Quiklang 3B Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803