Autotrain compatible Dataset:open-orca/openorca Endpoints compatible Gpt neox Instruct Lora Pytorch Region:us
Model Card on HF 🤗: https://huggingface.co/w601sxs/pythia-70m-instruct-orca-chkpt-64000
Pythia 70M Instruct Orca Chkpt 64000 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)
Pythia 70M Instruct Orca Chkpt 64000 Parameters and Internals
| Model Type |
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| Training Details |
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| Input Output |
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| LLM Name | Pythia 70M Instruct Orca Chkpt 64000 |
| Repository 🤗 | https://huggingface.co/w601sxs/pythia-70m-instruct-orca-chkpt-64000 |
| Model Size | 70m |
| Required VRAM | 0.2 GB |
| Updated | 2024-12-22 |
| Maintainer | w601sxs |
| Instruction-Based | Yes |
| Model Files | |
| Model Architecture | AutoModelForCausalLM |
| Is Biased | none |
| PEFT Type | LORA |
| LoRA Model | Yes |
| PEFT Target Modules | query_key_value |
| LoRA Alpha | 32 |
| LoRA Dropout | 0.05 |
| R Param | 8 |
Best Alternatives to Pythia 70M Instruct Orca Chkpt 64000
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Llama 3.1 Tango 70B | 0K / 3 GB | 124 | 7 |
| ...3 70B Instruct Uncensored Lora | 0K / 0.8 GB | 27 | 3 |
Note: green Score (e.g. "73.2") means that the model is better than w601sxs/pythia-70m-instruct-orca-chkpt-64000 .
Rank the Pythia 70M Instruct Orca Chkpt 64000 Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217