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Update README for Persian spaCy pipelines 

Improved README clarity and added installation instructions for Persian spaCy pipelines.
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# Persian (Farsi) pipelines for spaCy
Trained spaCy pipelines for Persianinstallable now. spaCy has
never shipped one, and `spacy.blank("fa")` gives you a tokenizer and stop words.
This pipeline built from UD_Persian-PerDT.
Trained spaCy pipelines for Persian, installable now. spaCy has never shipped an official one, and `spacy.blank("fa")` only gives you a tokenizer and stop words. These pipelines are built from the UD_Persian-PerDT treebank. choose between `fa_core_news_sm` (full syntax + NER) or `fa_dep_news_sm` (syntax only).
```bash
pip install https://huggingface.co/Phazel/fa_core_news_sm/resolve/main/fa_core_news_sm-any-py3-none-any.whl
```
```python
import spacy
nlp = spacy.load("fa_core_news_sm")
>>> import spacy
>>> nlp = spacy.load("fa_core_news_sm")
doc = nlp("محمدرضا شجریان در مشهد به دنیا آمد.")
print([(t.text, t.pos_, t.lemma_, t.dep_) for t in doc][:3])
# [('محمدرضا', 'PROPN', 'محمدرضا', 'nsubj'), ('شجریان', 'PROPN', 'شجریان', 'flat:name'), ...]
print(doc.ents) # (محمدرضا شجریان, مشهد) -> PER, LOC
>>> doc = nlp("محمدرضا شجریان در مشهد به دنیا آمد.")
>>> [(t.text, t.pos_, t.lemma_, t.dep_) for t in doc][:3]
[('محمدرضا', 'PROPN', 'محمدرضا', 'nsubj'), ('شجریان', 'PROPN', 'شجریان', 'flat:name'), ...]
>>> doc.ents
(محمدرضا شجریان, مشهد)
doc = nlp("شرکت ایران خودرو تولید را ۲۰ درصد افزایش می‌دهد.")
print([(e.text, e.label_) for e in doc.ents]) # ۲۰ درصد -> PCT
>>> doc = nlp("شرکت ایران خودرو تولید را ۲۰ درصد افزایش می‌دهد.")
>>> [(e.text, e.label_) for e in doc.ents]
[('۲۰ درصد', 'PCT')]
```
## Results
From `spacy benchmark accuracy`, stored in `metrics/`.