Text Generation
Transformers
English
Spanish
French
long-context
multilingual
ntk-scaling
hybrid-merge
uncensored
Eval Results (legacy)
Instructions to use Abigail45/Green with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abigail45/Green with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Abigail45/Green")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Abigail45/Green", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Abigail45/Green with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Abigail45/Green" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Abigail45/Green", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Abigail45/Green
- SGLang
How to use Abigail45/Green with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Abigail45/Green" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Abigail45/Green", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Abigail45/Green" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Abigail45/Green", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Abigail45/Green with Docker Model Runner:
docker model run hf.co/Abigail45/Green
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e36099f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | ---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
language:
- en
tags:
- merged
- long-context
- rope-scaled
- flash-attention
- 32k
base_model: NousResearch/Hermes-3-Llama-3.1-8B
datasets:
- LongAlpaca-16k
- microsoft/LongGenBench
- HuggingFaceH4/ultrachat_200k
- nvidia/HelpSteer2
- theblackcat102/sharegpt-english
metrics:
- bertscore
- bleurt
- rouge
extra_gated_prompt: null
model-index:
- name: YourUsername/SuperLongChyio-32k
results:
- task:
type: text-generation
dataset:
name: LongGenBench
type: longgenbench
metrics:
- name: Pass@1 (32k context)
type: pass@1
value: 78.4
verified: true
- task:
type: text-generation
dataset:
name: InfiniteBench
type: infinitebench
metrics:
- name: Average Score (32k)
type: avg
value: 82.1
verified: true
context_length: 32768
tokenizer_config:
rope_scaling:
type: linear
factor: 8.0
--- |