Instructions to use BigSalmon/DefinitionsSynonyms2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/DefinitionsSynonyms2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BigSalmon/DefinitionsSynonyms2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/DefinitionsSynonyms2") model = AutoModelForCausalLM.from_pretrained("BigSalmon/DefinitionsSynonyms2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use BigSalmon/DefinitionsSynonyms2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BigSalmon/DefinitionsSynonyms2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BigSalmon/DefinitionsSynonyms2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BigSalmon/DefinitionsSynonyms2
- SGLang
How to use BigSalmon/DefinitionsSynonyms2 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 "BigSalmon/DefinitionsSynonyms2" \ --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": "BigSalmon/DefinitionsSynonyms2", "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 "BigSalmon/DefinitionsSynonyms2" \ --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": "BigSalmon/DefinitionsSynonyms2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BigSalmon/DefinitionsSynonyms2 with Docker Model Runner:
docker model run hf.co/BigSalmon/DefinitionsSynonyms2
Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
given a definition, it will generate its corresponding word. there are several formats you can do it in:
|
| 2 |
+
|
| 3 |
+
```
|
| 4 |
+
part of speech- verb
|
| 5 |
+
definition: grow less in intensity or degree
|
| 6 |
+
ex. rather than leave immediately and be drenched, they waited for the storm to ________
|
| 7 |
+
synonyms: subside; moderate; decrease
|
| 8 |
+
antonyms: increase
|
| 9 |
+
word: abate
|
| 10 |
+
```
|
| 11 |
+
|
| 12 |
+
```
|
| 13 |
+
[adjective]
|
| 14 |
+
skeptical, disbelieving
|
| 15 |
+
Her eyes widened _____ly at the shocking news.
|
| 16 |
+
word: incredulous
|
| 17 |
+
```
|
| 18 |
+
|
| 19 |
+
```
|
| 20 |
+
the money or other means needed for a particular purpose
|
| 21 |
+
wordy: wherewithal
|
| 22 |
+
```
|
| 23 |
+
|
| 24 |
+
you can also fill in the blank:
|
| 25 |
+
```
|
| 26 |
+
due to the relentless pursuit of excellence, the [blank] of the firm is unquestioned [sep] preeminence [answer]
|
| 27 |
+
|
| 28 |
+
the hotel chain has [blank] its logo in an effort to appeal to younger travelers [sep] redesigned [answer]
|
| 29 |
+
```
|
| 30 |
+
|
| 31 |
+
to generate definitions, too:
|
| 32 |
+
```
|
| 33 |
+
harass | (v.) to disturb, worry; to trouble by repeated attacks
|
| 34 |
+
syn: annoy, pester, bedevil, beleaguer
|
| 35 |
+
|
| 36 |
+
inhibit | (v.) to restrain or hold back; to hinder or arrest; to prohibit
|
| 37 |
+
syn: repress, check, suppress
|
| 38 |
+
ant: foster, promote, expedite, facilitate
|
| 39 |
+
```
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
informal definitions:
|
| 43 |
+
```
|
| 44 |
+
synonyms: digression, extraneous, tangential.
|
| 45 |
+
description: when something is irrelevant but mentioned anyways.
|
| 46 |
+
|
| 47 |
+
***
|
| 48 |
+
|
| 49 |
+
synonyms: botched, fumbled, was unequal to the task, did not rise to the occasion.
|
| 50 |
+
description: did a really bad job at handling something.
|
| 51 |
+
```
|
| 52 |
+
|
| 53 |
+
```
|
| 54 |
+
description: did a really bad job at handling something.
|
| 55 |
+
synonyms: botched, fumbled, was unequal to the task, did not rise to the occasion.
|
| 56 |
+
|
| 57 |
+
***
|
| 58 |
+
|
| 59 |
+
description: when something is irrelevant but mentioned anyways.
|
| 60 |
+
synonyms: digression, extraneous, tangential.
|
| 61 |
+
```
|
| 62 |
+
|
| 63 |
+
```
|
| 64 |
+
question: michael is an ardent supporter of his presidential candidate.
|
| 65 |
+
what does "ardent" mean in the context of the selection?
|
| 66 |
+
answer: enthusiastic
|
| 67 |
+
``
|